Evaluation of Data Sources for National Manpower Planning and Monitoring Essay

Custom Student Mr. Teacher ENG 1001-04 9 April 2016

Evaluation of Data Sources for National Manpower Planning and Monitoring

Malaysia’s government agencies collect information directly from individuals and businesses to generate statistics that feed into the national’s labour market information. Major sources of data in any statistical system are from surveys, censuses and administrative data. Administrative data is defined by The Statistical Data and Metadata Exchange (SDMX 2009) as the information and data derive from an administrative source. Administrative source is a data holding containing information collected and maintained by and observatory party for the purpose of implementing their administrative roles. The cost of collecting administrative data is relatively cheaper compared to conduct separate censuses and surveys to collect similar information. As a by-product of the administrative process and not generally designed for statistical purposes, administrative data are potentially rich source of information for compiling any socio economic factors indicators. Objective

The objectives of this exercise are:

Scope of Study
This study is expected to review and analyze existing administrative data sources provided by: * Ministry of Human Resources (MOHR)
* Social Security Organization (SOCSO)
* Department of Labour (JTK)
* Department of Statistics, Malaysia (DOSM)
* Economic Planning Unit (EPU)
Developments In The Labour Market
Recent development in the world’s economies, beginning from the collapse of major banks in the United Sates in 2008 and the default of European national debts has brought an unprecedented level of risk and volatility into the labour market. Malaysia, as an export- oriented nation faces significant threat due to the uncertainties in the western economies, the traditional market for the nation’s exported goods. Fortunately, this downtrend is offset by a significant development in trades with Asian partners, significantly China. Coupled with healthy support for the prices of major commodities, the uncertainties in the international labur market managed to be mitigated by these emerging factors. Planning and monitoring of the labour market,in partclar to ensure that demand and supply in the labour market are properly and efficiently matched has become an increasing vital mission in face of the market volatilities. This objective is supported and pursued in this study and the preparation of this report. Our approach is based on monitoring and matching the demand and supply of labour as shown in the following diagram. Purpose Of Labour Market Indicators

Defining effective labour market strategies at the country level requires first and foremost the collection, dissemination and assessment of
up-to-date and reliable labour market information.Once a strategy is decided, continuing information and analysis are essential to monitor progress towards goals and to adjust policies where needed. Labour market information and analysis must be viewed as the cornerstone for developing integrated strategies to promote standards and fundamental principles and rights at work, productive employment, social protection and dialogue, as well as to address the cross-cutting themes of gender and development. Data Sources

The role of the data sources is to provide data for the purpose of producing the desired results. Two types of data sources are covered by this study, they are * Detailed Data Sources
* Summary Data Sources
Detailed data sources contain detailed particulars of individuals and organisations in their datasets. The data sources include SOCSO Registration Forms for both employers and employees, SOCSO claim forms, and various forms submitted to the Manpower Department (JTK). Summary data sources consist of labour market and relevant economic statistics that do not provide detailed particulars of employers and employees. They include survey and census reports such as the National Population Census and the Labour Force Survey from the Department of Statistics. A description of the data sources for labour market indicators and statistics covered by the scope of this study follows: Ministry of Human Resources

The Ministry of Human Resources is the government agency primarily entrusted to plan and manage all issues regarding manpower in the country. The stated vision and mission of the Ministry are as follows:

Vision
To be the leading agency in the development and management of a World Class Workforce.

Mission
* To develop a workforce that is productive, informative, discipline, caring and responsive to the changing labour environment towards increasing
the economic growth and hence create more job opportunities. * To encourage and maintain conducive and harmonized industrial relation between employers, employees and trade unions for the nation’s economic development and wellness of people. * To uphold social justice and ensure harmonious industrial relations through solving industrial dispute between employer and employee and awarding collective agreement. * To ensure trade unions practice democracy, orderly and is responsible to assist achieving the objective of industrial harmony. * To be the leader in development of nation’s human resources. * To ensure safety and health of workforce is assured.

* To develop skilled, knowledgeable and competitive workforce in a harmonious industrial relations with social justice.

Roles and Responsibilities
The roles and responsibilities of the Ministry are stated as * To update and implement labor policies and laws to create efficient, productive and discipline workforce with positive values and good work ethics. * To update and implement occupational safety and health policies and laws to ensure a healthy and safe work environment. * To efficiently manage and independently resolve industrial dispute between employer and employee in order to create a conducive work environment. * To monitor and facilitate development and movement of trade unions to be orderly for the benefit of the nation. * To manage international relations in Labor Management field, technical co-operation in labor related matters and human resources development. * To encourage and coordinate tripartisme among employees, employers and Government and to create harmonized relation toward Vision 2020. * To plan and develop human resource through control and labor market analysis to formulate policies relating to employment, development of skilled workforce and productivity linked wage system. * To create job opportunities and job placement.

* To update and implement National Vocational Training Policy and strategies that will fulfill the training needs in the private sector. * To revise, update and develop the syllabus of skills training (NOSS), Skills
Certification System (MOSQ) and skills standard for implementation. * To update and effective implementation of social safety facility to ensure sufficient safety net for workers.

Core Values
Core values that are imparted and uphold by the citizens of MOHR towards achieving the vision are: * Justice and Fairness
To appreciate and practice principle of justice and fairness to uphold social justice for the wellbeing of all. * Harmonious
To ensure harmonious industrial relations among employers, employees and trade unions for the development of the nation and well being of the citizens. * Tripartisme
To ensure close relationship in formulating and implementing policies, laws and regulations for the benefit of all. * Well being and Safety
To practice safety and health in a workplace to ensure a conducive and productive workplace. * Continuous Learning
To place importance on continuous learning through training and skills upgrading to ensure employability of competent and competitive workforce. * Caring
To provide social security protection for well being of employee, family, society and country.

The areas of interest and concern of the Ministry are expressed on their website as follows: Labour environment and employment trend is forever changing due to domestic and also global influence. Creating, establishing and maintaining job opportunities in conducive investment climate is important in ensuring healthy working environment and thus benefits the manpower. Improving working environment through efficient management will contribute to the realization of decent work fro employees. * Globalization and Labor Environment Changes

Globalization and economic liberalization has created a borderless labor market. Telecommunication and multimedia development had widened and improved management concept to fulfill stakeholders’ and customers’ demands. * Creating Attractive Investment Climate and Maintaining Competitiveness
Planning of national development and achieving the target of Vision 2020 has to consider global and regional development. A conducive investment climate environment, quality and competent workforce, labor policies and work place environment must maintain its competitiveness to attract investors and thus, creating new job opportunities. * Establishing a Dynamic Labour Market

Changes in employment pattern requires various new skills to be adapted to the new work force. Skills training must be able to produce skilled workers in order to fulfill labor market that applies the rapid use of technology. * Creating Balance Between Flexibility and Security in Human Resources Management In maintaining the National economy in the global competitiveness, it is important to make sure labor policies and national industrial relation will balance the rights and benefits of employers and employees so that a conducive investment climate can be established and the welfare of workers are maintained. * Labor Mobility

Globalization had created a borderless world and interdependency had caused unlimited labor migration. Massive entrance of unskilled migrant workers into the national labor market caused huge impact to the local labor market because they are willing to accept low salary suitable with their skills. Strategies and policies must be revised to overcome this challenges. * Harmonious Working Environment

Disputes and conflicts between employers and employees are unavoidable, thus, it is important to balance the rights and interests of both parties in maintaining harmonized industrial relation. Only with this co-operation, a conducive working environment for workers is guaranteed and hence increase the companies’ performance and productivity. * Competency and Employability

The Government’s role in analizing the national employment market situation and identifying labor policy will overcome the weaknesses in creating job opportunities. Labor policy and skills development planning must aim to coordinate skilled workforce development to fulfill the employment needs. * National Social Safety System

Establishment of consistent social safety system in line with the economic development and nation social needs. The system should not become a barrier to employment or reduce companies’ competency but is to mainly provide social safety net and to assist workers. * Reducing Accidents at Workplace

Rapid development of employment market means there will be a tough challenge in tracking the problem of rising accident cases at workplace. Best practices in occupational safety and health (OSH) should be practiced at all work premises to achieve zero accidents goal. SOCSO

SOCSO (Social Security Organization) or otherwise named as PERKESO (Pertubuhan Keselamatan Sosial Malaysia) was formed in 1971 with an aim of providing social security for workers. The organization operates social security schemes, registers employers and employees, collects contributions and disburse benefits. In carrying out its functions, SOCSO administers, enforces and implements the Employees’ Social Security Act, 1969 and the Employees’ Social Security (General) Regulations 1971. The Social Security Organization provides social security protection by social insurance including medical and cash benefits, provision of artificial aids and rehabilitation to employees to reduce the sufferings and to provide financial guarantees and protection to the family. An employee employed under a contract of service or apprenticeship and earning a monthly wages of RM3,000 and below must compulsorily register and contribute to SOCSO regardless of the employment status whether it is permanent, temporary or casual in nature. An employee must be registered with the SOCSO irrespective of the age. SOCSO only covers Malaysian workers and permanent residents. As a result, foreign workers are protected under the Workmen’s Compensation Act 1952. Nevertheless, SOCSO does not cover the following categories of persons : * A person whose wages exceed RM3,000 a month and has never been covered before. * Government employees.

* Domestic servants employed to work in a private dwelling house which includes a cook, gardeners, house servants, watchman, washer woman and driver. * Employees who have attained the age of 55 only for purposes of
invalidity but if they continue to work they should be covered under the Employment Injuries Scheme. * Self-employed persons.

* Foreign workers.

For the purpose of SOCSO contribution, wages mean all remuneration payable in money to an employee. The following payments are considered as wages : * salary
* overtime payment
* commissions and service charge
* payment for leave, sick, annual, rest day, public holidays, maternity and others * allowances, shift, incentive, housing, food, cost of living and others. * Payments made to an employee paid at an hourly rate, daily rate, weekly rate, task or piece rate are also considered as wages.

However, the following payments are not considered as wages : * payments by an employer to any statutory fund for employees * mileage claims
* gratuity payments or payments for dismissal or retrenchment * annual bonus.

Employers are required to fill Employer Registration Form 1 and Employee Registration Form 2 for registration with SOCSO. Employer must fill both forms neatly providing complete details in a legible manner. A copy of the trading, business or company license has to be enclosed. The name of an employee has to be as per Identity Card. Both the new and old Identity Card numbers of the employee have to be entered. Thereafter, the duly filled forms and relevant documents should be sent to the SOCSO local Office which will then issue the employer with an employer’s Code Number within 1 month. This number will be used in all correspondence with SOCSO. Contributions should be made from the first month an employee is employed. Contributions can be made through appointed banks or through post offices in Sabah and Sarawak only. The detail records of contributions to SOCSO can be sent using * Computer tapes and diskettes

* Electronic data transfers
* Preprinted Form 8A
SOCSO reports of having over 347,000 active employers and 5.5 million active employees in its database in its Annual Report 2010. Total contributions collected in 2010 exceeds RM 2.2 billion. Over 340,000 receipients received various benefits in 2010 totalling over RM 1.6 billion. Administrative data relevant for analysis of Labour Market Information that can be obtained from SOCSO are SOCSO Employer Registration Form

Administrative data that can be obtained from Form 1 – SOCSO Employer Registration Form, is * Name of employer
* Company/ business registration number
* Address of employer
* Town (free text)
* Postcode (no State field)
* Telephone/ fax numbers
* e-mail address
* Year of registration
* Year of operation
* Type of ownership (sole proprietor/ partnership/ private limited company/ limited company/ others) * Type of industry (free text)
* Address of business location
* Date of first employee appointment
* Number of employees hired (cumulative to date of registration) * Salaries paid during month of registration
* Name, NRIC, address of owner/ managing director/ partner (combined free text) A sample of the form is included in Appendix 3.
SOCSO Employees Registration Form
Data that can be obtained from Form 2 – SOCSO Employee Registration Form, is * Name of employee
* NRIC number
* Date of birth
* Gender
* Ethnicity
* Date of employment
* Occupation (free text)
* Employer SOCSO Code
A sample of the form is included in Appendix 3.
SOCSO Monthly Contribution Form
Data that can be obtained from Form 8A – SOCSO Monthly Contribution Form is * Contribution month and year
* Payment type (cheque number/ cash)
* Employer code
* Employer name
* Employer address
* Employee name
* Employee NRIC number
* Employee date start/stop work
* Amount of contribution (no Salary field)
A sample of the form is included in Appendix 3.
Information on the SOCSO member/insured person (claims & benefits) SOCSO provides several types of claims and benefits for contributors. The claims data for these benefits can provide collaborative and additional information on employers and employees. These are the amongst claimable benefits provided by SOCSO

* Dependent Benefits
* Funeral Benefits
* Education Loan
* Permanent Disability Benefits
* Temporary Disability Benefits
* Accidental Death Benefits
Information that may be obtained from these claims include (depending on the nature of claim) information on the SOCSO member/insured person * Name of insured/employee
* NRIC number
* SOCSO number
* Date of accident/death
* Death certificate number
In the case of death, information on the claimant/ next-of-kin is also obtained * Name of claimant/ next of kin
* Relationship to member (widow/widower/eldest son/daughter/father/mother) * Name of dependents (aged 21 and below)
* NRIC of dependents
* Name of caretaker of dependents
* NRIC of caretaker
* Caretaker occupation
* Monthly income of caretaker
* Number of caretaker’s dependents
* Relationship to dependents
* Caretaker’s adddress
For permanent and temporary disabilities, information about the disabilities and a doctor’s testimony is also obtained * Name of attending doctor
* Nature of complaint
* History of accident
* Physical examination details
* Pre-existing conditions
* Investigation results (lab test/ x-ray/etc)
* Diagnosis
* Treatment
* Period of medical leave
* Other remarks
For permanent and temporary disabilities, salary details for the last six months are obtained * Month and yesr
* Salary
* SOCSO contribution paid
Manpower Department (JTK)
The Manpower Department is the primary government agency that administers and manages human resources in the country. It owns and manages a few major sources of administrative and statistical data pertaining to the Labour market. These are: * National Employment Return (NER)

* Registration of Vacancies From Employment Agencies P. U (A) 214 * Registration of Applicants For Employment P.U (A) 214
* Registration of Job Applicants From The Disabled (Borang P) * Registration of Employers For The Disabled (Borang M)
The National Employment Return (NER) is treated both as a data source and data destination in this study. That is, as a data source, we explore how detailed information collected in the National Employer Return can be used to provide Labour Market Information Indicators and Statistics. As a data destination, we explore how administrative data from other sources can be used as to fill up some of the data required in the NER. The other data sources mentioned above does not solicit data as detailed as the National Employment Returns. The statistical and administrative data available from all the sources cited above are as follows where data from the National Employment Return is detailed out separately Copies of these forms are included in Appendix 3.

The manpower Department also operates a variety of programs under Jobs Services which registers applicants and job vacancies ad matches them. The programs under Jobs Services are: * JobsMalaysia Portal

* Jobs Placement Program (3P)
* Employer Registration Program
* Job Applicant Registration Program
* Vacancy Confirmation Program
* Career Information Center
* Career Guidance and Lectures
The programs had achieved over 400,000 placements with 218,000 registered employers and 550,00 actively searching applicants. Employers registered with these programs comprise of the following government agencies * Rubber Industry Smallholders Development Authority (RISDA) * Public Wotks Department (JKR)

* Inland Revenue, Malaysia
* Skill Development Fund Corporation (PTPK)
* Ministry of Communication and Culture
* Ministry of Health
* Federal Agriculture Marketing Agency (FAMA)
* Handicraft Development Corporation (Kraftangan Malaysia) * Armed Forces
* Construction Industry Development Board
* Putrajaya Corporation
* etc
while private sector employers registered with the programs include * Tenaga Nasional Berhad
* MPH Bookstores
* Sime Darby Group
* Ayamas
* etc
The JobsMalaysia Portal collects a wide range of data pertaining to employers, job applicants and vacancies. It is mentioned in a separate section below Details of data obtained from the registration of employees and vacancies are JobsMalaysia Portal

The JobsMalaysia Center, which serves its services through the JobsMalaysia Portal, is a one-stop centre that provides job search and matching services to Malaysian citizens. Services rendered are * Job Search

* Employee Recruitment
* Promoting Job Opportunities
* Career Counselling and and Guidance
* Data Collection on Retrenchments and Dismissal
* Creation of Jobs through Employer Relations

JobMalaysia conducts activities to collect information on the Labour Market as follows * Registration of Employers
* Registration of Job Applicants (including students who are bout to enter the Job Market i.e. Final Year Students) * Registration of Vacancies
* Matching of Candidates to Jobs and Job Placements, on weekly, monthly and annual basis * Matching of jobs for applicants from Special Focus Groups 1. Disabled applicants
2. Pensioners
3. Youths
4. Unemployed graduates
5. Ex-convicts
6. Ex-drug addicts

In particular, JobsMalaysia is involved in preparing and furnishing information regarding the Labour Market in the following areas * Job Seekers
* Employers
* Job Opportunities/ Vacancies
* Job Placements
* Employment Trends
* Retrenchment Information
* Projections
Employer Information
The portal caters for the following types of employers
* Individuals
* Enterprises, Partnerships and Companies
* Associations, Embassies, International Associations
* Government Agencies
The following information is collected from employers during the registration process * Employer name
* Address
* Postcode
* Territory/ Division
* State
* e-mail address
* Web Address
* Phone and Fax Numbers
* Industry and Sub-Industry
* Whether interested or not to hire diasabled
Employee Information
The following information collected from employees during the employee registration process * Name
* NRIC number
* Gender
* Marital status
* Race
* Nationality (for now restricted to Malaysians)
* Current job type (public sector/ private sector/ self-employed/ unemployed) * Address
* Postcode
* State
* District/ Division
* e-mail Address
* Telephone Number
* Mobile Phone Number
* Spoken Languages and Ability Levels (Fluent/ Good)
* Written Languages and Ability Levels
* Class of Driving License
* Other Licenses (e.g.. Scuba Diving)
* Applicant Category
7. School/ University Leaver
8. Seeking Career Enhancement
9. Laid Off Worker
10. Ex-Armed/ Police Force
11. Ex-Addict
12. Ex-Convict
13. Pensioner – Private Sector
14. Pensioner – Public Sector
15. Pensioner – Police
16. Disabled – Sight
17. Disabled – Speech
18. Disabled – Hearing
19. Midget
20. etc
* Education Level
21. Tertiary
22. Secondary
23. Primary
24. No Formal Education
* PMR/ SRP/ LCE Achievement
25. Year/ Grade
26. Subjects and Grade (maximum 10 only)
* SPM/ MCE/ SPM (V)/ SPVM Achievement
27. Year/ Grade
28. Subjects and Grade (maximum 10 only)
29. Bahasa Oral Test Result (Pass/ Fail)
* STPM/ STP/ HSC Achievement
30. Year/ Grade
31. Subjects and Grade (maximum 10 only)
32. Bahasa Oral Test Result (Pass/ Fail)
* PhD/ Masters/ Degree/ Diploma/ Certificate/ Final Year Student Achievement 33. Graduation Year
34. Qualification Level
35. CGPA/ PNGK
36. Instution
37. Is institution a foreign franchisee
38. Field of secialization
* Co-Curriculum Information
39. Sports field or Uniform Bodies/ Association/ Club
40. Level of achievement (International/ National/ State/ District/ Institution/ School) 41. Position (President/ Vice-President/ Secretary/ Treasurer/ Committee Member) 42. Work Experience (one only)

1. Company Name
2. Address
3. Position
4. Industry and Sub-Industry
5. Last Month Salary
6. Relevant Experiences (free text)
7. Unrelated Expereinces (free text)
8. Year Start
9. Year End
10. Reason For Leaving
Vacancy Information
The portal collects the following information on each vacancy * Name of position
* Description of position
* Length of vacancy
* Number of vacancies
* District and State of Vacancy
* Closing date for Applications
* Target Applicant Type (e.g. Pensioner)
* Working Hours (e.g. Normal)
* Offered Salary
* Gender
* Marital Status (e.g. Irrelevant)
* Contact Person, Phone Numbers and Cell Phone (2 persons) * Academic Achievement Level (Tertiary/ Secondary/ Primary/ No Formal Education) * Language Proficiency
* Age Group
* Vehicle Provided By Employer
* Type of Driving License Required
* Type of Professional License required
National Employment Returns
The National Employment Return is a special survey exercise undertaken bi-annually to collect data on the labour market. The first survey was conducted in 2007 and the latest in 2011. It’s coverage emphasises the characteristics of employers and employees, rather than employment and mismatches between labour demand and supply. Nevertheless, the parameters for data collected are detailed and exhaustive. The National Employment Returns are surveys conducted to obtain information on * Employers Profile and Composition

* Employees Profile and Composition
* Wage and Salary Levels
* Remuneraton practices
The sampling is based on employers registered with the Labour Market Database (LMD). The LMD contains data on establishments in the private sector and excludes * public sector organizations
* self-employed persons
* Non-Governmental Organizations (NGOs)
The workforce included in the survey covers
* Local Workers
* Expatriates
* Foreign Workers
For the 2009 Survey, 31,995 establishments (from 232, 437 employers in the LMD employing 3.35 million workers) were surveyed out of which 77% responded. The period covered was July to August 2009. It was a self-administered survey where respondents were sent the survey forms and after filing them themselves, the forms were returned to the Ministry of Human Resources. The unit of analysis is the private sector employers. Geographically, 84% of the samples were from Peninsular Malaysia and 8% each from Sabah and Sarawak. As noted by the survey “The distribution of employers across the sectors are uneven: 42% of them are in the distributive trade sector which includes wholesale and retail trade, repair of motor vehicles, motorcycles and personal and household goods. Despite having a large share of the employers, this sector accounts for only 21% of all employees. The manufacturing sector which had only 8% of all employers employed 28% of all employees.” Employers registered with the LMD consist mainly of small and medium scale enterprises (SME) with 78% of them employing less than 10 workers and 59% of them having a paid-up capital of less than RM100,000. The majority of employers in the LMD are registered as sole-proprietors with 64% of them being owned by non-bumiputeras. The survey is conducted under the provisions of Section 63 of the Employment Act 1955, Section 59 of the Sabah Labour Ordinance (Cap. 67) and Section 60 of the Sarawak Labour Ordinance (Cap. 76). The National Employment Return is divided into several areas Data on Employers

The National Employment Return is based on employers as it’s unit of sampling. Data on employers collected by the NER are * Company name
* Business Company Registration Number
* SOCSO Number
* EPF Number
* PSMB Registration Number
* Operational Address/ Postcode/ Town/ District/ State
* Phone/ Fax/ e-mail
* Correspondence Address/ Postcode/ Town/ District/ State * Company’s Capital – Authorized and Paid-Up
* Year Started Operating
* Location of Industry (Free Trade Zone/ Industrial Area/ Paid- Up Capital) * Year Commenced Business
* Equity Ownership
1. Bumiputra
2. Non-Bumiputra
3. Partnership between Bumi and Non-Bumi status companies 4. Local and Foreign Between Local and Foreign
5. Foreign Only
* Type of Ownership
* Sole Proprietorship
* Partnership
* Private Limited Company
* Public Limited Company
* Co-Operative
* Organisation
* Society
* Non-Profit Private Organization
* Method of Employing Workers
* Using Labour Contractor/ Outsourcing Company and Number Recruited * Part-Time Workers/ Home Working and Number Recruited
* Direct Intake/ Recruitment and Number Recruited
* Whether the Company has internal mechanism to prevent sexual harassment (Yes/ No) * Whether the company provide Employer/ Employee relation mechanism * Number of Special Class Employees

* By Category (Aborigine/ Disabled/ Ex-Drug Addicts/
* By Level (Executive/ Non-Executive)
* By Gender (Male/ Female)
* Employment Practices
6. Is bonus determined according to employee performance? 7. Is bonus based on Company Profit?
8. Is salary increment based on employee performance?
9. Does company pay on piece rate basis?
10. Does the company has an employer’s trade union? (provide name) 11. Does the company has an employee trade union? (provide name) 12. Whether the company pays the following allowances

13. Shift allowance
14. Attendance allowance
15. Incentive allowance
16. Food allowance
17. Transport allowance
18. Housing allowance
19. Laundry allowance
20. Cost of living allowance
21. Service allowance
22. Outstation allowance
23. Entertainment allowance
24. Telephone allowance
25. To enumerate 3 other allowances if practised (free text) 26. Whether the company provides the following facilities to employees 27. Housing
28. Hostel
29. Water supply
30. Electricity
31. Medical treatment
32. Dental treatment
33. Prayer room
34. Nursery
35. Sports and recreation facilities
36. Courses and training
37. Group insurance
38. Uniform subsidies
39. To enumerate 3 other benefits if practised (free text) * Industry (according to MSIC section and part)
* Products and services produced by Company (free text)
* Is product for local market? (yes/ no)
* Is product for export market? (yes/ no)
* Percentage of products exported
* Minimum and maximum bonuses paid for
* Executive staffs
* Non-executive staffs
* Medical benefits cost for the year
If the company provides training for employees, to provide (all free text) * Name of training course
* Cost per person
* Number of participants
* Venue of course
* State countries of export (free text)
Worker Particulars
The following aggregated data (in total and not by individual employee) is collected for local workers * Number of employees (by gender)
* Number of disabled employees (by gender)
* Total basic wages (by gender)
* Total overtime hours (by weekday, restday and public holiday) * Total overtime wages (by wekday, restday and public holiday) * Total cash allowances
* Average salary increment
The following aggregated data is collected for foreign workers (by country of origin) * Number of employees (by gender)
* Total basic wages (by gender)
* Total overtime hours (by weekday, restday and public holiday) * Total overtime wages (by wekday, restday and public holiday) * Total cash allowances
* Average salary increment
Whereby the data is categorized under the following groups of workers * Managers
* Professionals
* Technicians and Associates
* Clerical
* Services and Sales
* Skilled Agricultural, Forestry and Fishery Workers
* Craft and Related Trades Workers
* Plant and Machine Operators and Assemblers
* Elementary Occupation Workers
The number of workers is analyzed by the following categories * Age Group
1. Below 14
2. 14 – below 16
3. 16 – below 18
4. 18 – below 25
5. 25 – below 40
6. 40 – below 55
7. 55 – below 58
8. 58 – below 60
9. 60 – below 65
10. 65 and above
* Local workers by racial breakdown
11. Malay
12. Chinese
13. Indians
14. Other Bumiputeras (e.g. Orang Asli)
15. Sabah Citizen (all Sabah Citizens working in Peninsular Malaysia, bumiputra and non-bumiputra) 16. Sarawak Citizen (all Sarawak citizens working in Peninsular Malaysia, bumiputra and non-bumiputra) 17. Others

* Non-Citizen Workers
18. Expatriates (Non-citizen workers working in Malaysia in top management level/ management and professional or technical skills posts which require experience and related technical skills, approved by the relevant Expatriate Committee (EC) 19. Foreign Workers (Non-citizen workers who do not have any professional qualification, experience and technical skills Projected new jobs and manpower requirements

* Name of occupation
* Status of position (permanent, temporary or contractual * Academic qualifications (if job requirements SPM or equivalent and above) *
Offered salary (workers without experience)
* Offered salary (workers with experience)
* Number of workers needed for next 2 years
Note that that survey collects only the aggregated data (e.g. number of workers) in each category cited above. It does not collect detailed employee data such as name and NRIC number. Projection of Manpower Requirements

The survey collects data on projected manpower requirements for the next two years following the survey. Particulars collected are * Job Title (free text)
* MASCO Code
* Academic Qualifications (PMR/ SRP/ LCE; SPM; MCE/ STPM/ HSC and equivalent/ Diploma/ Degree/ Master Degree/ PhD * Skill Level (Malaysian Skill Certificate Levels 1 to 8 – SKM1- SKM8) * Techical Skills (free text e.g. Carpentry, air-conditioner, etc) * Soft Skills (free text e.g. Communcation skill, Management skill, etc) * Year

* Number of workers
Wage Particulars
Particulars of wages are collected from employers according to the MASCO categories of occupation (Major Groups and Sub- Major Groups). Employers return the number of employees falling in each Salary Range.The data is analysed into * Occupation (MASCO Major Group and Sub-Major Group)

* Local Worker, Expatriate or Foreign Worker
* Race (Malay, Chinese, Indian, Other Bumiputras, Sabah Citizen, Sarawak Citizen, Others) * Salary Band
1. Below RM350
2. RM 350-399
3. RM 400-549
4. RM 550-699
5. RM 700-999
6. RM 1,000-1,499
7. RM 1,500-1,999
8. RM 2,000-2,499
9. RM 2,500-2,999
10. RM 3,000-3,999
11. RM 4,000-4,999
12. RM 5,000-6,499
13. RM 6,500-7,999
14. RM 8,000-10,999
15. RM 11,000-13,99
16. RM 14,000 and above
The starting wage for each occupation can also be obtained by * Occupation (MASCO Major Group and Sub-Major Group)
* Local Worker, Expatriate or Foreign Worker
* Race (Malay, Chinese, Indian, Other Bumiputras, Sabah Citizen, Sarawak Citizen, Others) Labour Market Database
The Labour Market Database (LMD) provides a rich source of information on various aspects of the labour market. The range of information in the LMD covers the following Register of Employment
The Register of Employment (3.1) consists of the a number of reports regarding employers. These are Places of Employment
The Places of Employment Report (3.1.1) summarizes the number of employers by * Industry
* Office
* State
* Head Office
and provides the number of registered places of employment according to * as at beginning of month
* newly registered
* recently closed
* as at end of month
as well as the number of workers by the following categories * 0 workers
* 1 – 20 workers
* 21 – 100 workers
* 101 – 1000 workers
* more than 1001 workers
Basic Information On Employers
The Information on Employers Report (3.1.2) provides a list of employers with
the following details * Industry/ Office/ State/ Head Office
* File No
* Name
* Location
* Phone Number
* Fax Number
* Industrial Area Code
* Type of Primary Product
* Market
* Equity Ownership
* Type of Ownership
Number of Employers and Workers by Industry
The Number of Employers and Workers by Industry Report (3.1.3) summarizes the following statistics * Number of Employers
* Number of Workers
by Industry Types
Number of Local Workers By Type of Job and Industry
The Number of Local Workers By Type of Job and Industry Report (3.1.4) summarizes the number of workers by the following categories * Type of Industry, Office, State, Head Office
* Type of Job
* Ethnicity
* Gender
And into the following sub-classes
* Adult
* Diasabled
* Ex-Addicts
* Children
* Adolescent
* Part-Timers
Number of Foreign Workers by Type of Job and Industry
The Number of Foreign Workers by Type of Job and Industry Report (3.1.5) summarizes the number of workers by * Type of Industry/ Office/ State/ Head Office
* Type of Job
* Country of Origin
* Gender
Wages and Overtime by Job category and Type of Industry
The Wages and Overtime by Job category and Type of Industry Report (3.1.6) summarizes the following the following information * Number of workers
* Average basic wages
* Average wage
* Average overtime hours
* Average Overtime wages
by the following categories
* Local/ Foreign/ Local and Foreign Workers
* Type of Industry/ Office/ State/ Head Office
Basic Plantation Data
The Basic Plantation Information Report (3.1.7) lists plantations with the following details * Primary crop
* File no
* Plantation name
* Location address
* Acreage
* Number of local workers by gender
* Number of foreign workers by gender
Summary Informaion on Plantations
The Summary Information on Plantations Report (3.1.8) summarizes the following information on plantations * Primary crop
* Office
* State
* Head office
* Number of plantations
* Total acreage
* Number of local workers by gender
* Number of foreign workers by gender
* Total number of workers by gender
Monitoring of Terminations
The Monitoring of Termination (3.2) consists of the following reports Terminations by type of industry, citizenship and gender
The Terminations by type of industry, citizenship and gender (3.2.1) report summarizes the number of workers terminated by * Type of termination
* Type of industry/ office/ state/ head office
* Number of employers
* Number of employees before termination, analysed into
1. Local and Foreign
2. Gender
* Number of employees terminated, analysed by
3. Local and foreign
4. Gender
Reduction of wages by Industry, job category, citizenship and gender The Reduction of wages by Industry, Job category, citizenship and gender report (3.2.2) summarizes the following information * Type of industry/ office/ state/ head office

* Job category
* Number of employers
* Number of employees before action analysed into
1. Local and foreign
2. Gender
* Number of employees affected by action
3. Local and foreign
4. Gender
Payment of statutory retrenchment benefits
The Payment of statutory retrenchment benefits report (3.2.3) summarizes the following information * Number of employers
* Number of workers
* Amount that should be paid
* Amount actually paid
* Balance unpaid
* Percentage paid
analysed by
* Type of employment
* Industry/ office/ state/ head office
Payment of statutory retrenchment benefits by job category
The Payment of statutory retrenchment benefits by job category report (3.2.4) summarises the following information * Type of termination
* Job category/ office/ state/ head office
* Number of employers
* Number of employees
* Amount to be paid
* Amount paid
* Balance unpaid
* Percentage paid
Reasons For Termination
The Reasons For Termination Report Report (3.2.5) summarizes the number of employers and workers involved in terminations categorized by * Type of termination
* Job category/ office/ state/ head office
* Reason for termination
* Type of termination
Termination of Workers Due To Complete Closure/ Downsizing
The termination of Workers Due To Complete Closure/ Downsizing Report (3.2.6) summarizes the following information * Number and percantage of employers
* Number and percentage of workers
Analyzed by
* Cause for termination (complete closure/ downsizing)
* Reason for cause of termination
Number of Employers and Employees Involved in Terminations
The Number of Employers and Employees Involved in Terminations Report (3.2.7) summarizes the number of employers and employees involved in terminations analyzed into * Month/ office/ state/ head office

* Termination of workers
* Voluntary termination
* Temporary termination
* Salary reduction
Number or Workers Terminated by Job Category
The Number of Workers Terminated by Job Category Report (3.2.8) summarizes the number of workers terminated by * Type of termination/ office/ state/
head office
* Job category
* Local or foreign
* Gender
Inspection of Workplaces
The Inspection of Work Places Register consists of the following reports Inspection Report
Inspection Summary
Arrears Discovered During Inspection
Inspections by Industry Sizes
Inspections on Plantation Quarters
Handling of Complaints
The Handling of Complaints Register consists of the following reports Information on Complaints Received and Resolved By Industry and Time Lapse Number of Issues in Worker Complaints
Number of Issues in Labour Law Offenses
Arrears in Complaints
Handling of Labour Cases and Demands
Types of Claims
Cases and Claims Resolved by Type of Demands
Statistics on Enforcement of Labour Court Orders in Magistrate and Session Courts Statistics on Enforcement of Labour Court Orders in Magistrate/Session Courts Status of Labour Cases/ Claims by Sections and Ordinance

Status of Labour Cases/ Claims
Number of Labour Cases/ Claims Pending by Time Lapsed
Number of Labour Cases/ Claims Pending By Time Lapsed
Status of Labour Cases/ Claims by Sections
Status of Labour Cases/ Claims Resolved by Officers In Charge Information on Labour Cases/ Claims Received and Resolved By Industry and Time Spent Appeals on Labour Cases and Claims
Applications to Hire Foreign Workers/ Immigrants/ Expatriates The Applications to Hire Foreign Workers/ Immigrants/ Expatriates register consists of the following reports Number of Applications for AP, New
Licenses, Renewals and Replacements by Offices Number of Applications for AP and Licenses By Turnaround Times Number of APs/ Workers Approved and Rejected by Offices

Number of New Licenses, Licenses Under New APs, Renewals and Replacements Approved and Rejected Number of New Licenses, Renewals and Replacements Approved and Rejected by Industry Number of AP, New Licenses and Renewals Cancelled by Reasons Number of Foreign Workers in Approved Licenses By Industry and Jobs The Number of Foreign Workers in Approved Licenses by Industry and Jobs Report (3.6.7) summarises the number of foreign workers analysed by * Industry

* Job Types
* Malaysian citizens
1. Peninsular
2. Sabah
3. Sarawak
* Foreign workers by countries of origin
Number of Local Workers Compared to Foreign Workers Employed Under Section 119 Labour Ordinance The Number of Local Workers Compared to Foreign Workers Employed Under Section 119 Labour Ordinance Report (3.6.8) lists the following particulars * Names and addresses of employers

* Industry
* Job types
* Number of local workers
* Number of workers by state and country of origin
4. Peninsular
5. Sabah
6. Other countries
Number of Local Workers Compared to Foreign Workers Employed Under Section 119 Labour Ordinance Chapter 76 Sarawak by Industry and Countries of Origin The Number of Local Workers Compared to Foreign Workers Employed Under Section 119 Labour Ordinance Chapter 76 Sarawak by Industry and Countries of Origin Repoprt ( 3.6.9) summarizes the following statistics by * Industry

* Number of workplaces
* Number of local workers by
1. Peninsular Malaysia
2. Sabah
3. Sarawak
* Number of Foreign workers by countries of origin
Statistics on Number of Local Workers In Comparison to Foreign Workers In Sarawak by Country of Origin The Statistics on Number of Local Workers In Comparison to Foreign Workers In Sarawak by Country of Origin Report (3.6.10) summarizes the number of local and foreign workers in Sarawak by * Type of industry/ office/ state/ head office

* AP approval
* Quota approved
* Number of workers by
4. Sarawak
5. Sabah
6. Peninsular
7. Other countries of origin
* Number of workplaces

Workers’ Compensation Claims
Number of cases Reported and Status of Wokers’ Cases
Number of Reported Cases and Amount of Workers’ Compensation Information on Workers’ Compensation Received and Settled
Number of New Cases Received by Industry
Number of Cases by Types of Case and Year Received
Prosecutions
Prosecution Summary
Sexual Harrassment Cases
Monthly Report on Sexual Harrassment
Monthly Report on Preparations and Implementation of Internal Mechanisms Against Sexual Harrasment in the Workplace Complaints of Sexual Harrasments Received and Settled
Compounds
Statistics on Compounds by Number of Admissions, Industry and Offenses Number of Admissions Agreed and Amount of Compound by Industry and Offenses Visits and Promotional Activities
Promotion/ On-Site Counselling/ Labour Education etc
Promotion of Internal Mechanism and PAKK
Approval of Plans for New Buildings/ Renovations
Number of New Buildings and Renovation Plans Approved
Number of Approved New Buildings and Renovations Constructed Number of New and Renovation Plans for Nurseries Approved
Number of New and Renovation Plans for Housings Approved and CFs Issued Number of Nurseries from ARE, CFs and Promotional Activities Applications for Certificates of Fitness
Number of CFs for New Buildings and Renovations Issued
Number of New Buildings and Renovations for Which CFs had been Issued Employment of Foreign Workers
Job Types of Foreign Workers by Sectors and Countries of Origin List of Employers Without Insurance Coverage
Overtime Work and Job Types by Industry
Release of Contract Letters
Report on Release of Contract Letters
Issuance of Work Permits
Status on Issuance of Work Permits
The Status on Issuance of Work Permit Report (3.16) summarises the number of Work Permits by * Type of Work Permit/ Office/ State/ Head Office
* Number Not Completed Brought Forward
* Number Received
* Number of Applications Completed in
1. 1 Month
2. 2 Months
3. 3 Months
4. More than 3 Months
* Number Not Completed Carried Forward
List of Employers Approved Under Section 34 Labour Act 1955
The List of Employers Approved Under Section of Labour Act 1955 Report
(3.16.2) lists employers with the following particulars * By type of industry/ office/ state/ head office
* File no
* Employer name
* Number of local workers
* Number of Foreign workers
* Number of Women workers in 2 shift industries
5. Local workers
6. Foreign workers
* Number of Women workers in 3 shift industries
7. Local workers
8. Foreign workers
* Shift allowance rate
* Allowance rate for 2nd shift
* Allowance rate for 3rd shift
* Type of facility
Types of Wages Deduction Permits
The Types of Wages Deduction Permits Report (3.16.3) summarises the number of permits by * Reasons for deduction/ office/ state/ head office
* Number not completed brought forward
* Number received
* Number of cases completed in
9. 1 month
10. 2 months
11. 3 monthsc
12. More than 3 months
* Number not completed brought forward
Processing of Work Permits Under Labour Act
The Processing of Work Permits Under Labour Act Report lists the number of work permits by * Reasons for deduction/ office/ state/ head office
* Number not completed brought forward
* Number received
* Number of cases completed in
* 1 month
* 2 months
* 3 monthsc
* More than 3 months
* Number not completed brought forward
Advisory Services for Labour Department
Report on Advisory Services
Management of Foreigm Labour
The Labour Department plays key role in the management of foreign labour in the country with respect to * the enforcement of labour laws
* programs to upgrade the labour standards
* management of workers
* other management services
Statutory Inpections are carried out by the Labour Department with th following objectives * to ensure adherence to laws
* monitoring and early prevention of legal offences
* educating workers and employers on labour related matters * collecting labour data for planning and legal purposes
Four types of inspections are carried
* development inspections
* audit inspections
* estate inspections
* inspections on employers of foreign labour
The Labour Department is also empowered to issue permits which gives exemptions to employers from specific requirements of Labour Law to optimize labour usage, increase worker productivity and maintain labour standards. Sources of Information on Foreign Workers that can be tapped are Health Insurance Scheme For Foreign Workers

With effect from January 2011, employers of foreign workers are required to obtain health insurance for their foreign workers. Only plantation workers and domestic maids are exempted from this scheme. Employers seeking to deduct the cost of health insurance from their workers’ saaries are required to submit the following information to the Labour Department. However, once approval had been granted, the same employers do not need to make apply the same for new labour. Nevertheless, they are required to maintain records for inspection purposes. * Name of employer

* Address of employer
* Telephone number
* Fax number
* Officer in charge at employer’s office
* Type of business
* Existing number of workers, broken down into
1. Foreign workers
2. Local workers
* Number of workers involved in the application, broken down into 3. Foreign workers
4. Local workers
* Name of insurance company
* Name of insurance scheme
* Nature of benefits to workers
* Salary deduction period
* Monthly deduction amount
Others
The Manpower Department also collects data that is relevant on Labour Market through other minor processes such as those pertaining to employment agencies and the handicapped. These are:
* Registration of Vacancies from Employment Agencies
* Registration of Applicants for Employment
* Registration of Job Applicants from Disabled
* Registration of Employers for the Disabled
Data from these forms are described below:
Data on Employers
Data solicited from these sources contain the following information on employers * Name of employer
* Address
* Telephone/ fax numbers
* Nature of Business
For employers of disabled persons, additional information is collected * Registered address
* Type of industry
Data On Employees/ Job Applicants
Data solicited from these sources contain the following information on job applicants and employees * Name
* Address
* Date of Registration
* NRIC No
* Gender
* Qualification and Experience
For applicants that are successfully matched to employment placements * Name of employers
* Address of employers
* Starting salary
* Work position
For disabled persons, additional information is obtained
* Marital status
* Name of Association
* Contact person for association
* Type of disability
* Cause of disability
* Type of support equipment used
* Name of next-of-kin
* Address of next-of-kin
* Allergies (if any)
* Qualifications
* Experience
* Soft Skills
* Status of applicant (seeking employment/ working/ studying/ training/ others) * Salary range requested (per annum)
* Date employment is required
* Type of work seeked
* Location (area/ state) of work requested
* Special facilities requested (transportation/ accommodation/ railings/ toilets/ etc) Data On Job Positions/ Vacancies
Data from these sources contain the following information on job positions and vacancies * Name of Position
* Location of Work
* Job Requirements/ Pre-requisites
* Qualifications and Experience Requirements
* Number of Positions
* Date of Vacancy

For vacancies for the disabled, additional information is collected * Name of positions
* Number of vacancies (by gender and type of disability)
* Minimum salary offered
* Minimum qualifications/ skills/ experience required
* Special amenities provided (transportation/ accomodation/ railings/ toilets/ etc) * Working environment (air-conditioned/ hot air/ dusty/ fans) Department of Statistics Malaysia
The Department of Statistics is the leading producer of statistics for the country and the official producer of national statistics. It produces a number of reports on surveys and census in various areas: * Economy and Business Statistics

1. Agriculture
2. Business Indicators
3. Construction
4. External Sector
5. Manufacturing
6. Mining and Quarrying
7. Prices
8. Services
* Social and Demographic Statistics
9. Household Income and Expenditure
10. Labour Force aqnd Social Statistics
11. Population and Demography
Following are data and publications from the Department of Statistics that are relevant to Labour Market Information Indicators and Statistics Labour Force and Social Statistics
The Department of Statistics conducts the following surveys pertaining to the
Labour Force: Labour Force Survey
The Labour Force Survey Report, Malaysia, presents the annual data on the characteristics of the labour force, unemployment and the structure of employment based on the monthly survey conducted by the Department of Statistics, Malaysia. It includes information on employment and labour force at state level. The Labour Force Survey uses the personal interview method during which trained interviewers visit households in selected living quarters to collect information on all household members including their demographic particulars. Field checks are undertaken to identify and correct an error or omissions. All household members will be asked the following information: * relationship to household head

* sex
* age
* ethnic and citizenship
* marital status
* educational attainment
For those aged 15 years and over, their activity status – either employed, unemployed or outside labour force – will be determined. Information collected from the employed include whether they had working or not during the reference week, the number of hours worked, occupation, industry and status in employment, and if they have worked less than 30 hours per week, reasons and willingness to accept additional work. If they have not been working during the reference week but have a job to return to, the reasons for not working would be sought. The following questions will be sought to those who are unemployed: * action taken to look for work

* work experience
* duration of unemployment
Those who are classified outside labour force will be asked to state the reasons for not seeking work and working experience. The Labour Force Survey covers both urban and rural areas of all states in Malaysia. The survey population is defined to cover persons who live in private living quarters and hence exclude persons residing in institutions such as hotels, hostels, hospitals, prisons, boarding houses and military barracks. The survey
comprises the economically active and inactive population. To measure the economically active population, the Labour Force Survey uses the age limit of 15 to 64 years. The economically active population comprises those employed and unemployed whereas those who are inactive is classified as outside labour force. The frame used for the Labour Force Survey is from the National Household Sampling Frame (NHSF) which is made up of Enumeration Blocks (EBs) created for the 2000 Population and Housing Census. EBs are geographically contiguous areas of land with identifiable boundaries. On average, each EB contains about 80- 120 living quarters. Generally, all EBs are formed within gazetted boundaries, i.e. within administrative districts, mukim or local authority areas. Information obtained from the survey provides input for analysing the labour market situation, policy formulation as well as planning, implementing and monitoring programmes related to human resource development. Analysis of Labour Force

The Labour Force Survey reports on several Key Indicators as follows Working Age Population
The population of working age persons is reported by the following components * Labour Force
1. Employed Persons
2. Unemployed Persons
* Outside Labour Force
Labour Force Participation Rate (LFPR)
The Labour Force Participation Rate of a particular category is the number of persons in the labour force in the specified category divided by the total number of persons in the working age (15 to 64) group in the same category, expressed as a percentage. These are further analysed as follows

By Sex and Age Group
The categories for age groups are
* 15-24
* 25-34
* 45-54
* 55-64
By Educational Attainment
The categories for Educational Attainment are
* No formal education
* Primary
* Secondary
* Tertiary
By Ethnic Groups
The categorization by ethnicity is as follows
* Malaysian Citizens
1. Bumiputera
1. Malay
2. Other Bumiputera
2. Chinese
3. Indian
4. Others
* Non-Malaysian Citizens
Employed Persons
The number of employed persons is reported by the following modes of analysis By Ethnic Groups
The categorization by ethnicity is as follows
* Malaysian Citizens
* Bumiputera
* Malay
* Other Bumiputera
* Chinese
* Indian
* Others
* Non-Malaysian Citizens
By Educational Attainment
Analysis by Educational Attainment are as follows
* No formal education
* Primary
* Secondary
* Tertiary
By Sex and Age Group
Analyse by Age Group
* 15-24
* 25-34
* 45-54
* 55-64
By Occupation
* Legislators, senior officials and managers
* Professionals
* Technicians and associate professionals
* Clerical workers
* Service workers and shop and market sales workers
* Skilled agricultural and fishery workers
* Craft and related trade workers
* Plant and machine operators and assmblers
* Elementary occupations
By Industry
* Agriculture, hunting and forestry
* Fishing
* Mining and Quarrying
* Manufacturing
* Electricity, gas and water supply
* Construction
* Services
* Wholesale and retail trade, repair of motor vehicles, motorcycles and personal and household goods * Hotels and restaurants
* Transport, storage and communications
* Financial intermediation
* Real estate, renting and busines activities
* Public administration and defence; compulsory social security * Education
By Status In Employment
* Employer
* Employee
* Own account worker
* Unpaid family worker
Unemployment Profile
The unemployment rate is the proportion of unemployed population to the total population in labour force, expressed as a percentage. For any specific category, the unemployment rate is the Unemployment Rate By Stratum

* Urban
* Rural
Number and Unemployment Rate by Sex
Percentage Distribution of Unemployed Persons By Age Group
The number of unemployed persons is grouped by the following categories * Below 20 years
* 20-24 years
* 25-29 years
* 30 years and older
Percentage Distribution of Unemployed Persons by Educational Attainment Educational Attainment is categorized as
* No formal education
* Primary
* Secondary
* Tertiary
Potential Population Entering The Labour Market
This indicator represents the number and percentage distribution of persons outside the labour market. It is analyzed as follows By Sex
By Reasons For Not Seeking Work
* Schooling
* Housework
* Going for further studies
* Disabled
* Not interested
* Retired
* Others
By Highest Certificate Obtained
* UPSR/UPSRA or equivalent
* PMR/SRP/LCE/SRA or equivalent
* SPM or equivalent
* Degree, diploma, certificate, STPM or equivalent
1. STPM or equivalent
2. Certificate
3. Diploma
4. Degree
* No certificate
* Not applicable
By Working Experience
* Never worked before
* Worked before
Number of Employed Persons With Tertiary Education
This indicator reorts the number of employed persons who have tertiary education and is analyzed as follows By Occupation
* Legislators, senior officials and managers, professionals and technicians and associate profesionals * Legislators, senior officials and managers
* Professionals
* Technicians and associate professionals
* Others
* Clerical workers
* Service workers and shop and market sales workers
* Skilled agricultural and fishery workers
* Craft and related trade workers
* Plant and machine operators and assmblers
* Elementary occupations
Labour Force Statistics
The Labour Force Survey reports the following statistics
Population
The total number of persons in the population
Working Age Population
The number of persons f working age (15-64) in the population) Labour Force
The number of persons in the labour force, broken down into
* Number of employed persons
* Number of employed
Outside Labour Force
Number of persons who are outside the labour force
Labour Force Participation Rate
The labour force participation rate
Characteristics of Employed Persons
The number of employed persons is analyzed as follows
By Strata
* Urban
* Rural
By Age Group
* 15-19
* 20-24
* 25-29
* 30-34
* 35-39
* 40-44
* 45-49
* 50-54
* 55-59
* 60-64
By Occupation
* Legislators, senior officials and managers
* Professionals
* Technicians and associate professionals
* Clerical workers
* Service workers and shop and market sales workers
* Skilled agricultural and fishery workers
* Craft and related trade workers
* Plant and machine-operators and assemblers
* Elementary occupations
By Industry
* Agriculture, hunting and forestry
* Fishing
* Mining and quarrying
* Manufacturing
* Electricity, gas and water supply
* Construction
* Wholesale and retail trade; repair of motor vehicles, motorcycles and personal and household goods * Hotels and restaurants
* Transport, storage and communications
* Financial intermediation
* Real estate, renting and business actiities
* Private households with employed persons
* Extra-territorial organizations and bodies
By Status In Employment
* Employers
* Employees
* Own Account Workers
* Unpaid Family Workers
By Educational Attainment
* No formal education
* Primary
* Secondary
* Tertiary
By Highest Certificates Obtained
* UPSR/UPSRA or equivalent
* PMR/SRP/LCE/SRA or equivalent
* SPM or equivalent
* Degree, diploma, certificate, STPM or equivalent
1. STPM or equivalent
2. Certificate
3. Diploma
4. Degree
* No certificate
* Not applicable
By Marital Status
* Never married
* Married
* Widowed
* Divorced/ permanently separated
Definitions
These are how the Labour Force Survey Report defines the relevant terms
Stratum
The classification of geographical areas by stratum is as follows * Metropolitan – 75,000 and over
* Urban large – 10,000 and 74,999
* Urban small – 1,000 – 9,999
* Rural – All other areas
For the purpose of urban/ rural analysis, the stratum are collapsed as follows * Urban = Metropolitan + Urban Large
* Rural = Urban Small + Rural
A stratified two-stage sample design is adopted. There are two levels of stratification, that is: * Primary stratum – made up of the states in Malaysia
* Secondary stratum – made up of the urban and rural stratum as defined above Working Age
Working refers to those who are between 15 to 64 years age group during the reference week, who are either in or outside the labour force. Status
The Labour Force Survey uses the actual status approach, where a person is classified, on the basis of his labour force activity during the reference week. The activity status is categorized as follows Labour Force

Labour Force refers to those who, during the reference week, are in the 15 to 64 years age group (in completed years at last birthday)and who are either employed or unemployed. Employed
All person who, at any time during the reference week, worked at least one hour for pay, profit or family gain (as an employer, employee, own-account worker or unpaid family worker). Underemployed

Employed persons at work and who had worked less than 30 hours during the reference week because of the nature of their work or due to insufficient work and are able and willing to accept additional hours of work are considered underemployed but are nevertheless included in the employed category. Unemployed

The unemployed are classified into two categories
Actively Unemployed
All persons who did not work during the reference week but were available for work and actively looking for work during the reference week. Inactively Unemployed
These include persons in the following categories:
* persons who did not look for work because they believed no work was available or that they were not qualified, * persons who would have looked for work if they had not been temporarily ill or had it not been for bad weather, * persons who were waiting for answers to job applications, * persons who had looked for work prior to the reference week. Outside Labour Force

All persons not classified as employed or unemployed as stated above were classified as outside the labour force. Included were housewives, students (including those going for further studies), retired or disabled persons, and those not interested in looking for a job. Hours Worked

Refers to total hours worked during the reference period.
Household
A person or group of related and unrelated persons who usually live together and make common provision for food and other essentials of living. Ethnic Group
The classification of ethnic group is based on the classification as used in the 1991 Population Census. In this classification the ethnic group is categorised within Malaysian citizens after separating those who are non- citizens. The classification is as follows: * Malaysian citizens

* Bumiputera
* Malay
* Other Bumiputera
* Chinese
* Indian
* Others
* Non Malaysian citizens
Marital Status
Marital status is classified into
Never Married
Refers to persons who report themselves as never married
Married
Refers to persons who are currently married at the time of enumeration. The term, “married” includes those married by law or by religious rites or are living together by mutual agreement. Widowed
Refers to those who have not remarried after the death of the spouses at the time of enumeration. Divorced/ Permanently Separated
Refers to those whose marriages are annulled through divorce by law or religious arrangement or separated for a long duration without any possibility of reconciliation. Educational Attainment
Refers to the hghest certificate obtained from the public or private educational institution that provides formal education. Starting from year 2008, classification of highest certificate obtained is according to the International Standard Classification of Education (ISCED). No Formal Education

Refers to persons who never attended school in any of the educational institutions that provide formal education. Primary
Refers to those whose highest level of education attained is from Standard 1 to 6, or equivalent. Secondary
Refers to those whose highest level of education attained is from Form 1 to 5 (including remove class), GCE ‘O’ Level or equivalent. Includes basic skill programmes in specific trades and technical skills institution whereby the training period is at least six months i.e. GIATMARA Tertiary

Refers to those whose highest level of education is above Form 5. Highest Certificate Obtained
This refers to the highest certificate obtained from the public or private educational institution that provides formal education. Starting from year 2008, clasification of highest certificate obtained is according to the International Standard of Education (ISCED). UPSR/UPSRA or equivalent

Refers to Ujian Penilaian Sekolah Rendah/ Ujian Penilaian Sekolah Rendah Agama or equivalent PMR/SRP/LCE/SRA or equivalent
Refers to Penilaian Menengah Rendah, Sijil Rendah Pelajaran, Lower Certificate of Education, Sijil Rendah Agama or equivalent SPM or equivalent
Refers to Sijil Pelajaran Malaysia or equivalent (Senior Cambridge Certificate, GCE O Level and Malaysia Certificate of Vocational Education). Includes basic skill certificate obtained from specific trades and technical skills institutions whereby the training period is at least six months i.e. GIATMARA certificate. STPM or equivalent

Refers to Sijil Tinggi Persekolahan Malaysia, Higher School Certificate or equivalent (Sijil Tinggi Agama and GCE A Level). Certificate
Refers to certificate obtained from college, polytechnic or other institutions which offers formal education. Duration of certification should not be less than six months. Diploma
Refers to diploma or equivalent certificate obtained after category (iii), (iv) or (v) from university, college or polytechnic prior to a degree qualification. Degree
Refers to degree (Bachelor, Masers or Ph.D) obtained from public or private higher institution or equivalent. No Certificate
Refers to those persons who are currently attending school or who have completed schooling without receiving any certificate. Not Applicable
Refers to those persons who have no formal education.
Status In Employment
Status in employment refers to the position or status of an employed person within the establishment or organization for which he/she worked. Employed persons are classified according to the following employment status: Employer

A person who operates a business, a plantation or other trades and employs one or more workers to help him. Employee
A person who works for a public or private employer and receives regular remuneration in wages, salary, commission, tips or payment in kind. Own Account Worker
A person who operates his own farm, business or trade without employing any paid workers in the conduct of his farm, trade or business. Unpaid Family Worker
A person who works without pay or wages on a farm, business or trade operated
by another member of his family. Occupation
Occupation is classified in the Labour Force Survey Report according to the “Malaysian Standard Classification of Occupations (MASCO) 1998” vased on the “International Standard Classification of Occupations (ISCO-88)”. Industry

In the Labour Force Survey Report, industry is classified according to the “Malaysia Standard Industrial Classification (MSIC) 2000” published by the Department of Statistics, Malaysia based on the “International Standard Industrial Classification of All Economic Activities (ISIC), Revision 3”. Migration Survey

The Migration Survey is carried out simultaneously with the Labour Force Survey and covers the same survey population i.e. urban and rural areas for all states in Malaysia. The population covered consists of persons aged one year and over residing in selected private living quarters in Malaysia. The report is published annually. The main objective of Migration Survey is to provide estimates of population movements and trends at state level. In addition, this survey also aims to obtain the socio-economic information of migrants and non- migrants such as age, sex, employment and type of occupation at the place of destination. The scope of migration data in the survey is limited to fixed-term migration. Respondents are asked for the usual place of residence on two specific reference dates which are exactly one year apart. A change in the usual place of residence locality between these two points constitutes migration. Wages and Salary Survey

Salaries and Wages Survey is conducted using household approach via the Labour Force Survey. Basic wage rate can be obtained from this survey and is used to measure wage differentials and gender wage gap. Salaries and wages information is only collected from respondents aged 15 and over with the status in employment of either “Government Employee” or “Private Employee”. The survey is conducted in January until June and the reference period is a month prior to the survey month. Labour Force Statistics

The Labour Force and Social Statistics is represented by a time series data obtained from the Labour Force Survey and prsented annually since 1982 with
the exception of 1991 and 1994 during which the survey was not conducted. The data repesents estimations of

* Labour Force
* Distribution of Employment by Occupation and Industry
* Unemployment
Labour Force is taken as those on the age groups between 15-64 years old and includes both employed and unemployed persons. Employed persons are all those who were worked for at least 1 hour during the reference week. It also includes those who have employment but did not work because of injuries, holidays and similar reasons. Unemployed persons are classified into two groups which are * the actively unemployed and

* the inactively unemployed.
The actively unemployed include all persons who did not work during the reference week but were available for work and actively looking for work during the reference week. * The inactively unemployed persons include the following categories: * Did not look for work because they believed no work was available or they were not qualified; * Would have looked for work if they had not been temporarily ill or had it not been for bad weather; * Waiting for answers to job applications; and

* Looked for work prior to the reference week.
In addition to the Labour Statistics time series, the Department of Statistics also publish the following time series data * Total number of paid workers
* Total amount of salaries and wages paid
* Value of gross output
* Cost of input
* Value add
* Value of assets owned
by the following industries
* Mining and quarrying
* Construction
* Services (sub-categorised into sub-services)
* Manufacturing
Population and Demography
The Department of Statistics produces the following census (every 10 years) and time series on the population National Population and Housing Census
The Population and Housing Census is conducted once in every 10 years and updated annually. The last Census was conducted in 2000. The Census was conducted using face to face interview. Information collected includes the number of persons and households together with a wide range of demographic, social and economic characteristics. Information on housing stock, structural characteristics of houses as well as amenities in living quarters is collected. The Census data is published in various reports according to special topics which is made available at the Users Service Unit of DOSM. The statistics on housing and population will be used as inputs in the development planning, formulation of policies by the government as well as other users. The next Census is expected to be carried out in 2010. Population Estimates

Quarterly Population Estimates are published and analysed by the following dimensions By Ethnic Group and Sex
Ethnic groups are categorized into
* Malaysian citizens
1. Bumiputera
1. Malay
2. Other Bumiputera
2. Chinese
3. Indian
4. Others
* Non Malaysian citizens
By Age Groups
Age groups are set at 5 year intervals
* 0-4
* 5-9
* 10-14
* 15-19
* 20-24
* 25-29
* 30-34
* 35-39
* 40-44
* 45-49
* 50-54
* 55-59
* 60-64
* 65-69
* 70-74
* 75+
Population Projections
For projections and forecasting purposes, the following data is also published on quarterly basis * Natural Increase and Crude Rate of Natural Increase by Ethnic Group * Life Births and Crude Birth Rate By Ethnic Group

* Deaths and Crude Death Rate By Ethnic Group
* Life Expectancy By Ethnic Group And Sex
Employment
Employment statistics are published every quarter as follows Employment By Industry
Number of persons employed by quarters in the following industries * Agriculture, forestry and fishing
* Mining and quarrying
* Manufacturing
* Electricity, gas, steam and air-conditioning supply
* Water supply; sewerage, waste management and remediation activitie * Construction
* Services
1. Wholesale and retail trade; repair of motor vehicles and motorcycles 2. Transportation and Storage
3. Accommodation and Food Service Activities
4. Information and communications
5. Financial and Insurance/Takaful Activities
6. Real Estate Activities
7. Professional, Scientific and Technical Activities
8. Administrative and Support Services Activities
9. Public Administration and Defence; Compulsory Social Security 10. Education
11. Human Health and Social Work Activities
12. Arts, Entertainment and Recreational
13. Other Service Activities
* Activities of Households As Employers
* Activities of Extraterritorial Organisations and Bodies

Employment By Occupation
Number of persons employed by quarters in the following occupations * Managers
* Professionals
* Technicians and associate professionals
* Clerical support workers
* Service and sales workers
* Skilled agricultural, forestry and fishery workers
* Craft and related trades workers
* Plant and machine operators and assemblers
* Elementary occupation
Households
Household Income And Basic Amenities Survey
The Household Income Survey (HIS) has been conducted by the Department of Statistics, Malaysia since 1973. However, starting from 1987, The Basic Amenities Survey was conducted together with Household Income Survey and known as Household Income/Basic Amenities Survey (HIS/BA) and is carried out once every 5 years. The latest HIS/BA survey was carried out in 2009. The main objectives of the HIS/BA survey are to measure the economic well-being of the population; collect information on income distribution pattern of household classified by various socio-economic characteristics; identify the poor groups; collect information on basic amenities of household; and study the effects of the implementation of national development program. The name of the household head is collected in this survey, together with key
identification data such i.e. NRIC number. Household Expenditure Survey

The Household Expenditure Survey (HES) was first conducted in the year 1957/58. Beginning 1993/94 it was carried out at an interval of five years and subsequently in 1998/99. The recent survey was undertaken in 2009/2010. The survey covers private households in urban and rural areas. The main objective of HES is to collect information on the level and pattern of consumption expenditure by households on a comprehensive range of goods and services. This information serves as the basis for determining the goods and services to be included in the basket of the Consumer Price Index (CPI). It is also used to update the CPI weights where the CPI is a measure of the average rate of change in prices of a fixed basket of goods and services which represents the expenditure pattern of households in Malaysia. Business

Business Tendency Survey
The Business Tendency Survey is conducted quarterly by the Department of Statistics, Malaysia since 2004. The survey gathers views from the senior management of 465 prominent establishments in four major sectors in Malaysia namely * industry,

* construction,
* wholesale & retail trade and
* services.
The main characteristic of this survey is to collect information regarding the direction of change of key economic variables. The Business Tendency Survey collects qualitative information from business managers on their assessment of the business performance for the past quarter and the expectations for the next three and six months. The information is useful for monitoring the current economic situation and its impact on the Labour Market environment. Identity of the respondents’ businesses and their actual and projected sentiments about the economic environment is collected for the immediate past and projected future quarters. The respondents are surveyed by the following sectorial categories * Agriculture

* Mining, electricity and water
* Manufacturing
* Construction
* Wholesale and retail trade
* Hotels
* Services (Transportation, Communication, Insurance, Real Estate and Information & Communication Technology) * Finance
Economic Census
The Department of Statistics conduct Economic Census every 5 years by the following indutsries Agriculture
Data collected by the Department of Statistics pertaining to employment in the agricultural sector are as follows Economic Census 2011 – Agricultural Sector
The Economic Census 2011 – Agricultural Sector is conducted under the Statistics Acts, 1965 (Revised 1989), which provides heavy penalties for non- compliances. Where data is not available, respondents are required to provide estimates. The census collects detailed data every 5 years and in the instance of the 2011 census, it is conducted in respect to the reference year 2010 from business owners involved in the agricultural sector, namely those who are involved in the following activities: * Crops

* Livestock
* Fisheries
* Forestry and Logging
As can be seen above, the scope of the census is limited only over businesses in the agricultural sector. Manufacturing Industries
Data collected by the Department of Statistics pertaining to employment in the manufacturing industry are as follows Monthly Manufacturing Survey
The Department of Statistics, Malaysia (DOSM) conducts the Monthly Manufacturing Survey, 2011 commencing reference month January 2011. The survey covers 120 out of a total of 197 industries in the Manufacturing Sector (based on the Malaysia Standard Industrial Classification, 2000). This is a mail and web base enquiry survey. Survey questionnaires are mailed to respondents at the beginning of the year and the time given to complete and return a copy of the questionnaire or submit through online survey for each reference month is by/before the 10th of the following month (example:
for reference month January 2011, the due date for submission is 10th February 2011). The main objective of the survey is to collect information required by the government for current economic analysis, formulation and implementation of policies and also in monitoring the performance of the Manufacturing Sector. The information collected is published in two monthly publications namely “Index of Industrial Production, Malaysia” and “Monthly Manufacturing Statistics, Malaysia” which are both available at the Users’ Service Unit of Department of Statistics, Malaysia. Annual Survey of Manufacturing Industries

The Department of Statistics, Malaysia (DOSM) conducts the Annual Survey of Manufacturing Industries 2010 for reference year 2009. The survey covers 259 industries in the manufacturing sector (based on the Malaysia Standard Industrial Classification, 2008). This is a mail enquiry survey. Respondents are given one month to complete and return the questionnaires to the Department. The main objective of the survey is to collect information pertaining to growth, contribution, composition and distribution of the manufacturing sector to assist the government in development planning and formulating policies. The data is also used for the compilation of national accounts, input- output tables and specific studies. In addition, the results are used by policy makers, economists, planners and academicians in economic projections and analysis. The information collected is published in the publication namely “Report on the Annual Survey of Manufacturing Industries” which is available at the Users’ Service Unit of DOSM. Economic Census 2011 Manufacturing Industry

The Department of Statistics, Malaysia (DOSM) has conducted the Economic Census 2011 of Manufacturing sector for reference year 2010. The census covered 259 industries from in the Manufacturing Sector (based on the Malaysia Standard Industrial Classification, 2008 ver. 1.0.). This is a mail enquiry census. Respondents were given one month to complete and return the questionnaires to the Department. The main objective of the census is to collect information pertaining to growth, contribution, composition and distribution of the manufacturing sector to assist the government in development planning and formulating policies. The data are also used for
the compilation of national accounts, input-output tables and specific studies. In addition, the results are used by policy makers, economists, planners and academicians in economic projections and analyses. Construction Industries

Data collected by the Department of Statistics pertaining to employment in the construction industry are as follows Construction Industries Survey
The Department of Statistics, Malaysia (DOSM) conducts the Construction Industries Survey for every two years. The survey covers 72 industries from the Construction Sector (based on the Malaysia Standard Industrial Classification, 2008). This is a mail enquiry survey. The respondents are the establishments primarily engaged in construction activities with the value of construction work done RM 500,000 and above. As such, the survey does not include the lesser successful establishments in the construction industry. The respondents are given 30 days to complete and return the questionnaires to the Department. The main objective of the survey is to collect information pertaining to growth, composition and distribution of output, value added, employment and other variables of the sector. The data are used to assist the government in development planning and formulating policies. The data can also be used by the private sector and individuals for economic analysis. Census of Construction Industries

The Department of Statistics, Malaysia (DOSM) conducts the Census of Construction Industries for every five years. The survey covers 72 industries from the Construction Sector (based on the Malaysia Standard Industrial Classification, 2008). This is a mail enquiry survey. The census covers establishments primarily engaged in construction activities. The respondents are given 30 days to complete and return the questionnaires to the Department. The main objective of the survey is to collect information pertaining to growth, composition and distribution of output, value added, employment and other variables of the sector. The data are used to assist the government in development planning and formulating policies. The data can also be used by the private sector and individuals for economic analysis. Mining and Quarrying

Data collected by the Department of Statistics pertaining to employment in the mining and quarrying industry are as follows Annual Census of Crude Oil and Natural Gas Mining Industries 2010 The Department of Statistics, Malaysia conducts the Annual Census of Crude Oil and Natural Gas Mining Industries 2010 for reference year 2009. The census covers Section B (Mining and Quarrying) based on the Malaysia Standard Industrial Classification, 2008. This census is a mail enquiry survey. Respondents are given two (2) months to complete and return the questionnaires to the Department. The main objective of the survey is to collect information pertaining to growth, contribution, composition and distribution of the crude oil and natural gas sector to assist government in development planning and formulating policies. The data are also used for the compilation of national accounts, input-output tables and specific studies. In addition, the results are used by policy makers, economists, planners and academicians in economic projections and analyses. The information collected is published in the publication namely Petroleum and Natural gas Statistics. Economic Census 2006 (Mining and Quarrying)

The Department of Statistics, Malaysia (DOSM) conducted the Economic Census (Mining & Stone Quarrying) for reference year 2005 which was carried out in 2006. The Mining Census was carried out since 1963, while The Stone Quarrying Census started since 1972. Since 2000, censuses of the mining and quarrying sectors have been carried out once in every 5 years. This census covers 25 industries in the Mining and Quarrying sector (based on the Malaysia Standard Industrial Classification, 2000). This is a mail enquiry census. Respondents were given one month to complete and return the questionnaires to the Department. The main objective of the census is to collect information pertaining to growth, contribution, composition and distribution of the mining and quarrying sector to assist the government in development planning and formulating policies. The data also can be used by the private sector and individuals for economic analysis. The information collected is published in the publication namely “Economic Census 2006 (Mining and Quarrying)” which is available at the Users’ Service Unit of DOSM. The respondents of the survey are categorised into 3 groups

* Mining
* Sand Mining
* Stone Quarrying
Services
The Department of Statistics Malaysia publishes several types of census for the services industry. These are * Monthly Survey of Distributive Trade – Monthly
* Quarterly Survey on Services – Quarterly
a) Food and Beverage Services
b) Information and Communication Services c) Accommodation Services
d) Transport Services
e) Education Services
f) Health Services
g) Professional Services
* Census/Survey of Services Establishments – Education i. Kindergartens – Biennial
ii. Primary schools – Biennial
iii. General secondary schools – Biennial
iv. Technical and vocational education – Biennial
v. Colleges – Biennial
vi.Commercial and other technical institutes – Biennial vii. Driving schools – Biennial
viii. Music and dancing schools – Biennial
ix. Others schools – Biennial
* Census/Survey of Services Establishments – Hospital/Healthcare i. Hospital – Biennial
ii.Maternity homes – Biennial
iii. Other healthcare services – Biennial
* Census/Survey of Services Establishments – Clinics – Biennial * Census/survey of Services Establishments – Architectural, engineering, surveying and other related technical consultancy services – Biennial * Census/Survey of Services Establishments – Accounting – Biennial * Census/Survey of Services Establishments – Legal – Biennial * Census/Survey of Services Establishments – Accommodation – Annually *
Census/Survey of Services Establishments – Real estate agents – Biennial * Census/Survey of Services Establishments – Stock, share & bond, commodity brokers & foreign exchange and money changers services – Biennial * Census/Survey of Services Establishments – Motion picture projection – Biennial * Census/Survey of Services Establishments – Advertising – Biennial * Census/Survey of Services Establishments – Information & Communication technology – Annually i) Telecommunication services

ii) Computer services
* Census/Survey of Services Establishments – Consultancy – Biennial * Census/Survey of Services Establishments – Sea transport – Annually i. Passenger vessel – Biennial
ii. Freight vessel – Annually
iii. Towing and pushing (vessel) – Annually
* Census/Survey of Services Establishments – Public bus – Biennial * Census/Survey of Services Establishments – Travel agency and tour operator * Census/Survey of Services Establishments – Air transport – Annually * Census/Survey of Services Establishments – Cargo, storage and haulage – Biennial * Census/Surveys of Services Establishments – Train – Biennial * Census/Surveys of Services Establishments – Inland water transport – Biennial * Census/Surveys of Services Establishments – Car parking – Biennial * Census/Surveys of Services Establishments – Highway operations – Annually * Census/Surveys of Services Establishments – Courier – Biennial * Domestics Tourism Survey (DTS) – Annually

* Homestay Census – Ad-Hoc
* Tourism Establishment Survey
i. Meeting, Incentive, Convention, Exhibition (MICE) – Annually ii. Personal Care & Spa activities (SPA) – Biennial iii. Recreational Activities – Biennial
iv. Museum activities – Biennial
v. Sport activities – Biennial
vi. Private vehicle for hire (except taxi) – Biennial Monthly Survey of Distributive Trade
Quarterly Surveys on Services
Census/ Survey on Service Establishments – Education
Census/ Survey on Service Establishments – Healthcare/ Hospitals Census/ Survey on Service Establishments – Clinics
Census/survey of Services Establishments – Architectural, engineering, surveying and other related technical consultancy services Subtopic
Economic Indicators
The Department of Standards publishes leading, coincide and lagging indicators on the Malaysian Economy Leading Indicators
The index of leading indicators, the components of which are adjusted for inflation, accurately forecasts the ups and downs of the business cycle up to 12 months preceding actual. Components of the leading economic indicators are: * Real Money Supply, M1

* KLSE Share Price Index, Industrial
* Real, Total Traded with Eight Major Partners
* CPI for Services, Growth Rate (Inverted)
* Industrial Material Price Index, Growth Rate
* Ratio of Price to Unit Labour Cost, Manufacturing.
* Housing Permits, Approved
* New Companies, Registered
Coincide Indicators
These are economic indicators that coincide with the current pace of economic activity to give the public a reading on whether the economy is expanding or contracting and at what pace. The components of the Index of Coincident Indicators are * Index of industrial production

* Real gross imports
* Real salaries and wages, manufacturing
* Total employment, manufacturing
* Real sales, manufacturing
* Real contributions, EPF
Lagging Indicators
The index of lagging indicators which confirms economic trends lag behind the actual pace of economic activity. The six components of the lagging
indicators are * 7-day call money, rate (inverted)

* Real excess leading to private
* Number of investment projects approved
* Number of defaulters, EPF (inverted)
* Number of new vehicles registered
Economic Planning Unit, Prime Ministers Department
The Economic Planning Unit (EPU) is the government agency responsible for developing economic plans for the nation. In doing so the EPU performs the following activities * Collects statistics and indicators

* Analyses information and produces historical time series * Produces forecasts and projections
* Develops economic and transformation plans

The EPU’s input for the labour market information includes information on * Economic forecasts and plans
* Population and labour force studies
* Transformation plans
* Statistics on up-skilling programs (under NKEA)

The EPU publishes statistics in the following areas
* Population and manpower
* National account
* Agricultural products
* Industrial output indicators
* Public services
* External trade
* Balance of payment
* Price indices
* Social indices
* Economic indices
* Selected world indices

Of these, the following sets provide directly relevant data on Labour Market
Information (number of workers) Population And Labour Force Studies
The Population and Manpower Statistics published by the EPU provide the following statistics * Population Size
1. By Age Group and Year (1891 – 2008)
2. 0 – 14
3. 15 – 64 (Working Age)
4. 65+
5. By Sex, Ethnic Group and Age (every 10 years where 2010 data is projected) 6. Age (Intervals of 5 years, from 0 to 70 and above)
7. Ethnic Groups (Malay, Other Bumiputras, Chines, Indians and Others) 8. By State
* Employment by Sector, Unemployment and Participation Rate by Year (1982 – 2007) * Data source from Department of Statistics
* Sectors are according to MIC 1972
* Agriculture, Livestock, Forestry and Fishing
* Mining and Quarrying
* Manufacturing
* Construction
* Electricity, Gas and Water
* Transport, Storage and Communications
* Wholesale & Retail Trades, Hotels & Restaurants * Finance, Insurance, Real Estate and Business Services
* Other services
* Immigrant Workers
9. By Country of Origin (1999-2008)
10. The countries of origin are: Indonesia, Bangladesh, Thailand, Philippines, Pakistan, Others 11. Sourced from Ministry of Home Affairs
12. By Sectors (1999-2008)
13. The sectors are: Maid, Manufacturing, Plantation, Construction, Services, Agriculture 14. Sourced from Ministry of Home Affairs
Economic Forecasts and Plans
Relevant statistics published by the Economic And Planning Unit, Prime Minister’s Department, Malaysia are Industry Production Indices
The Industry Production Indices is useful for determining
* Trends in production growth/ contraction
* Correlation between employment and production by industry * Projecting production and employment

The Industry Production Indices published by EPU are
* Sourced from the Department of Statistics
* Provides annual indices from to 2008
* Provides indices for the Mining, Manufacturing and Electricity Industries Statistics of Primary Agricultural Products
These statistics, sourced from the Department of Statistics, are published for the following agricultural products * Rubber
* Palm Oil
* Cocoa
* Forestry and Logging

And provide information (by year) on
* Number of Plantations
* Planted Hectarage (includes immature areas), by
1. Plantations
2. Smallholders
* Hectarage in Production
3. Production
* Yield Per Hectare
* Average Price
* Number of Workers Employed
Desired Outcome
Consolidating the indicators and statistics published in the data sources covered by the scope of this study and complementing them with additional indicators for a comprehensive and holistic representation of the Labour Market Information, the study produced the following data requirements that, if fulfilled, will cover the needs of the Key Indicators of the Labour Market (KILM) and the aforementioned reports and published statistics in a data warehouse combining detailed and aggregated or summarized data enabling 360-degree analysis with slice and dice and drill-through capabilities. The requirements are categorized into 4 areas of concern each with it’s own set of components * Employment Situation

* Indicators on Employment
* Indicators on Unemployment
* Unemployment Situation
* Indicators on Under-Employment
* Indicators on Un-Employment
* Demand For Labour
* Economic Indicators – Actual and Forecast
* Indicators on Manpower Shortage
* Supply Of Labour
* Indicators on Population
* Indicators on Education
* Indicators on Foreign Labour
Indicators, Statistics and Details
Summary Indicators and Statistics
The Labour Market Information (LMI) indicators and statistics can be categorised into the following Key Areas: * Employment Statistics – these data provide analytical information on employments. The components covered are * employee statistics (eg Age Groups, Race) and

* employer statistics (Size of Company, Type of Business) * Unemployment Statistics – these data provide analytical information on the unemployment and under- employment situations. The components covered are * population size

* unemployment statistics and under employment statistics * Labour Requirements – these data provide analytical information on the actual and projected demand for various types of labour/ manpower and gives insight into demands that are not met/ not projected to be met by available labour force. The components covered are * Economic forecasts and plans

* Information on manpower shortages
* Labour Supply – these data provide analytical information about expected availability of various types of labour/ manpower supply. Components covered are * Population growth projections
* Educational statistics
* Foreign Labour statistics, including statistics on Malaysians working or migrating abroad

The Indicators, used in combination with analytical dimensions in each Key Area above, fulfil the needs of the Key Indicator of the Labour Market (KILM) as well as the needs of the National Employment Returns and Labour Force Survey. In fact, they go beyond those in giving the capability to conduct a 360-degree analysis of the labour market information, with slice-and-dice and drill-up and drill-down capabilities. The following screenshots show some examples of a 360-degree analysis that is possible using Microsoft Excel and Business Intelligence dashboards with data coming from a data warehouse supporting the 360-degree analysis capability

Conducting 36-degree analysis using Excel with back-end data warehouse

A basic pie-chart drawn from the data Expand the data and view sub-totals

Drill-down the data into sub-categories Show interaction amongst multiple dimensions

Performance Dashboards using back-end data warehouse Employment Situation
Indicators and statistics on the employment situation cover situations where labour supply is matched with demand i.e. where labour is engaged in employment. These include indicators that analyse employment by characteristics of the employers, such as industrial sector, size, location etc and indicators that analyse the characteristics of employees such as demographic profiles, geographical distribution, education attainment etc. These indicators provide insight into active employers and employees in the
labour market Indicators On Employers

The indicators that provide insight into the characteristics of employers in the labour market.are * Number of employers
* Payroll costs incurred by employers
* Working hours set by employers
* Training budgets and costs incurred by employers

The indicators on employers are to be analyzed by the following dimensions * Geographical locations
* Industrial sectors
* Types of business ownership
* Equity ownership
* Size of paid-up capital
* Size of annual turnover
* Size of employed workforce
* Types of employment (direct recruits, outsourcing, part-time etc) * Compensation types practised (salaries, share of profits, bonuses, incentives, etc) * Compensation practices (rates schedule, employment benefits, promotions etc) Indicators On Employees

The indicators That provide insight into employees in the labour market are * Number of employees
* Amount of compensation received by employees, broken down into the following indicators * Total monthly compensation
* Manufacturing wage indices
* Occupational wage indices
* Hourly compensation costs
* Starting salaries
* Years in employment
* Hours of work
* Number of part-time workers
* Employment in the informal sector
* Labour productivity

These indicators are analyzed into the following dimensions
* Geographical locations
* Industrial sectors
* Countries of origin
* Employee gender
* Ethnicity
* Education attainment
* Years of experience
* Age groups
* Marital Status
* Employment status
* Occupation
* Skill types possessed (Civil Engineering, Mechanical Engineering, etc) * Soft skill types possessed (Level of literacy, inter-personal communication, information technology, etc) * Membership in special focus groups (Orang Asli, disabled, etc) Unemployment Situation

While indicators on the employment situation covers areas where demand and supply of labour are matched, indicators on the unemployment situation reports on situations of unemployment and under-employment due to mismatch of demand and supply of labour. In a particular economy, both employment and non-employment may occur at the same time. Non-employment may be caused by a mismatch of circumstances affecting demand and supply, for example demand for a particular type of skill set not be met by supply in a particular geographical area while there is an over- supply of the same skillset in another geographical area. The unemployment indicators consist of

Indicators On Under-Employment
These indicators consist of
* Number of persons who are under- employed (working less than 30 hours per week) * Period of time in under-employment

It is analyzed by
* Geographical locations
* Persons’ country of origin
* Gender
* Ethnicity
* Educational attainment
* Age band
* Employment Status
* Marital Status
* Skill types
* Soft skill types
* Special groups
* Length of time being under-employed (by time period bands) * Reasons for under-employment
* Willingness to work more hours if provided? (yes/no)
* Other major activities carried out during under-employment The indicator provide insight into the degree of severity of the under- employment situation, where it is happening (by geographical as well as demographical boundaries) and the underlying causes of under- employment; with emphasis on particular special focus groups. Indicators On Un-Employment

These indicators consist of
* Number of persons who are unemployed (working less than 1 hour per week) * Period of time in unemployment

Further sub-indicators that cover specific areas of interest for unemployment are * Youth Unemployment
* Long Term Unemployment
* Time Related Unemployment

These indicators are analyzed by
* Geographical locations
* Persons’ country of origin
* Gender
* Ethnicity
* Educational attainment
* Age band
* Employment Status
* Marital Status
* Skill types
* Soft skill types
* Special groups
* Length of time being unemployed (by time period bands)
* Reasons for unemployment
* Whether the person had been looking actively for a job? (yes/no) * Type of activities carried out during unemployment

The indicators provide insight into the degree of severity of the un-employment situation, where it is happening (by geographical as well as demographical boundaries) and the underlying causes of un- employment; with emphasis on particular special focus groups. Demand For Labour

The Employment and Unemployment/ Under-Employment Indicators report on the size of employment and unemployment situation, but does not provide coverage on the size of demand for labour especially unfulfilled demand for labour. This is an area of particular interest to the nation as it aspires to reach the status of a developed country. There exists pockets and niches of labour supply that face acute shortages. Some of these shortages threaten to delay the achievement of industrializing the country and transforming it into a more effective knowledge economy.. Thus the following set of indicators report on the demand for labour (met and un-met), and consists of Economic Indicators – Actual And Forecast

Economic activities of the country play a major influence on demand for labour in the market. In particular, the level of exports, trade surplus and direct investments determine the health of the economy and creation of jobs. The following economic indicators are the basic ones required for historical time-series and projecting planned and forecasted impact of the level of economic activity on demand for labour in the market * Number of businesses

* Size and growth of Gross Domestic Product
* Size of Imports and Exports
* Investments and Foreign Direct Investments
* Inflation Rate
* Government Budget
* Employment Elasticity Studies

To be relevant for labour market analysis, these indicators are at least analyzed * By geographical locations (e.g. States)
* By country of origin (for number of businesses, size of imports/ exports, Investments, etc) * By industrial sectors
Indicators On Manpower Shortages
While the economic indicators provide insight on the indirect impact of economic activity levels on the labour market, these indicators on manpower shortages provide coverage on actual shortages faced * Number of positions

* Length of time vacant

These are to be analyzed by
* Geographical location
* Industrial sector
* Educational attainment
* Skills required
* Soft-skills required
Supply Of Labour
While the indicators for Labour Demand covers unfulfilled demand for labour, and unemployment covers existing surplus of labour supply, the following indicators on the supply of labour cover future and anticipated labour supply. They include indicators on persons in the labour-supply stream (education statistics) as well as supply of foreign labour that both complements and competes against domestic supply. The indicators that report on the supply of labour consists of Indicators On Population

These indicators report generally on the population of the country and consists of * Total population size
* Size of labour force
* Size outside labour force
* Employment to Population Ratio
* Employment Elasticities
* Population Education Attainment and Illiteracy

These indicators are to be analyzed by
* Geographical locations
* Persons’ country of origin
* Gender
* Ethnicity
* Educational attainment
* Age band
* Employment Status
* Skill types
* Soft skill types
* Special groups
* Reasons for being outside the labour force (for indicator of people outside the labour force) Indicators On Education
The indicators on education report on future supply of labour by essential categories and consist of * Number of students
* Number of graduates
* Number of trainees
* Number of certificates issued
* Number of students working in the labour market

The indicators are to be analyzed into
* Geographical location of institutions
* Gender
* Ethnicity
* Skills/ Disciplines
* Soft-Skills Developed
* Educational Attainment
* Age Groups
* Employment status (for working students)

These indicators provide an insight into future entrants into the work force
by types and levels of skills, as well as other categories. Indicators On Foreign Labour
The indicators on foreign labour supply consists of
* Planned quota
* Number of persons (actual and forecasted)
* Number of cases of domestic labour outflow (locals working abroad)

These indicators are to be analyzed into
* Gender
* Country of Origin
* Age Group
* Education Attainment
* Skills Possessed
* Soft Skills Possessed
* Marital Status
Key Indicators For Labour Market (KILM)
KILM is a multi-functional research tool of the ILO consisting of county-level data on 20 key indicators of the labour market from 1980 to the latest available year. The first KILM was released about 10 years ago. It has since become a flagship product of the International Labour Office (ILO). The first Key Indicators of the Labour Market (KILM) was released in 1999. It has since become a flagship product of the International Labour Office (ILO) and is used on a daily basis by researchers and policy-makers throughout the world. At the national level, statistical information is generally gathered and analysed by statistical services and ministries. At the global level, the ILO plays a vital role in assembling and disseminating labour market information and analysis to the world community. The KILM is a collection of 20 “key” indicators of the labour market, touching on employment and other variables relating to employment (status, sector, hours, etc.), the lack of work and the characteristics of jobseekers, education, wages and compensation costs, labour productivity and working poverty. Taken together, the KILM indicators give a strong foundation from which to begin addressing key questions related to productive employment and decent work. The KILM is:

* a comprehensive database of country level data on 20 key indicators of the labour market from 1980 to the latest available year. In this context, the KILM can serve as a tool for policy makers and researchers in monitoring and assessing many of the pertinent issues related to the functioning of labour markets. * a source of the latest ILO world and regional estimates of employment and unemployment indicators. * a training tool on development and use of labour market indicators. Each indicator is accompanied by descriptions of the standard international definition of the concept and measurement procedures, guidelines on how the indicator can be used in analyses of labour market issues, and words of cautions on comparability limitations. Readers are guided on the value of using multiple indicators to develop a broader view of labour market developments. * highlights of current labour market trends. The trends identified in an analysis of each indicator accompany each indicator manuscript, with graphics to display results. * analysis of key issues in the labour market.

The Key Indicators for Labour Market Malaysia (KILMM) adopts the indicators from Internation Labour Organization (ILO) but excludes the following indicators * Employment In The Formal Sector
* Part Time Workers
* Manufacturing Wages Indices
* Occupational Wages Indices
* Hourly Compensation Costs
* Poverty, Working Poverty and Income Distribution
* Labour Productivity
* Employment Elasticities
On the other hand, KILMM adds another indicator to the set
* KILM 13: Inactive Rate
These indicators are summarised in their respective sections below, by referring to International Labour Organization(ILO), Department of Statistics Malaysia(DOSM). When the measures and dimensions identified in for the Summary Indicators and Statistics section above have been fulfilled, the requirements of the Key Indicators for the Labour Market (KILM) will also be fulfilled as KILM is a subset and may be calculated from the set of
measures and dimensions. Labour Force Participation Rate

The labour force participation rate is a measure of the proportion of a country’s working-age population that engages actively in the labour market, either by working or looking for work; it provides an indication of the relative size of the supply of labour available to engage in the production of goods and services. The breakdown of the labour force by sex and age group gives a profile of the distribution of the economically active population within a country. The labour force participation rate is calculated by expressing the number of persons in the labour force as a percentage of the working-age population. The labour force is the sum of the number of persons employed and the number of unemployed. The working-age population is the population above a certain age – ideally aged 15 and older – prescribed for the measurement of economic characteristics. number of persons employed and the number of persons unemployed. Thus, the measurement of the labour force participation rate requires the measurement of both employment and unemployment. Employment should, in principle, include members of the armed forces, both the regular army staff and temporary conscripts. The labour force participation rate is related by definition to other indicators of the labour market. The inactivity rate is equal to 100 minus the labour force participation rate, when the participation rate is expressed as a number between 0 and 100. KILM 13 shows the harmonized inactivity rates of persons according to the standardized age bands used in KILM. The employment-to-population ratio (KILM 2) is equal to the labour force participation rate after the deduction of unemployment from the numerator of the rate. The unemployment rate (KILM 9) is related to the labour force participation rate and employment-to-population ratio in such a way that two of them determine the value of the third. A comprehensive source of data for determining the labour force participation rate and related indicators is specialized surveys of households or individuals, often referred to as labour force surveys. Such surveys can be designed to cover virtually all the non-institutional population of the country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, unpaid family workers, casual workers and multiple jobholders. In addition, such surveys generally provide
an opportunity for the simultaneous measurement of the employed, the unemployed and the economically inactive in a coherent framework. Population censuses are another major source of data on the labour force and its components. The labour force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and do not allow detailed probing on the labour market activities of the respondents. The Labour Force Participation Rate is calculated as the Labour Force (being total Employed Persons plus Total Unemployed but available and willing to work) divided by Total Working Age Population. To compute the breakdown of the Labour Force Participation Rate by other dimensional parameters, such as gender, age group, educational attainment and ethnicity then the input parameters (Employed Persons, Unemployed Persons, Working Age Population) broken down by the dimensional parameters is needed. Employment-To-Population Ratio

The employment-to-population ratio is defined as the proportion of a country’s working-age population that is employed. A high ratio means that a large proportion of a country’s population is employed, while a low ratio means that a large share of the population is not involved directly in market-related activities, because they are either unemployed or (more likely) out of the labour force altogether. The employment-to-population ratio provides information on the ability of an economy to create employment; for many countries the indicator is often more insightful than the unemployment rate. Although a high overall ratio is typically considered as positive, the indicator alone is not sufficient for assessing the level of decent work or decent work deficit. Additional indicators are required to assess such issues as earnings, hours of work, informal sector employment, underemployment and working conditions. In fact, the ratio could be high for reasons that are not necessarily positive – for example, where education options are limited, young people tend to take up any work available rather than staying in school to build their human capital. For these reasons, it is strongly advised that indicators should be reviewed collectively in any evaluation of country-specific labour market policies. The concept that employment – specifically, access to decent work – is central to poverty reduction was firmly acknowledged in the framework of the Millennium
Development Goals (MDG) with the adoption of an employment-based target under the goal of halving the share of the world’s population living in extreme poverty. The employment-to-population ratio was adopted as one of four indicators to measure progress towards target on “achieving full and productive employment and decent work for all, including women and young people”. The employment-to-population ratio is the proportion of a country’s working-age population that is employed. The youth and adult employment-to-population ratios are the proportion of the youth and adult populations – persons aged, typically, 15 to 24 years and 25 years and over – that are employed. Employment is defined in the resolution adopted by the 13th International Conference of Labour Statisticians (ICLS) as persons above a specified age who performed any work at all, in the reference period, for pay or profit (or pay in kind), or were temporarily absent from a job for such reasons as illness, maternity or parental leave, holiday, training or industrial dispute.5 (See box 2.) The resolution also states that unpaid family workers who work for at least one hour should be included in the count of employment, although many countries use a higher hour limit in their definition. For most countries, the working-age population is defined as persons aged 15 years and older, although this may vary slightly from country to country. The ILO standard for the lower age limit is, in fact, 15 years. For many countries, this age corresponds directly to societal standards for education and work eligibility. However, in some countries, particularly developing ones, it is often appropriate to include younger workers because “working age” can, and often does, begin earlier. Some countries in these circumstances use a lower official bound and include younger workers in their measurements. Similarly, some countries have an upper limit for eligibility, such as 65 or 70 years, although this requirement is imposed rather infrequently. The variations on age limits also affect the youth and adult cohorts. Apart from issues related to age, the population base for employment ratios can vary across countries. In most cases, the resident non-institutional population of working age living in private households is used, excluding members of the armed forces and individuals residing in mental, penal or other types of institution. Many countries, however, include the armed forces in the population base for their employment ratios even when they do not include them in the employment
figures. In general, information for this indicator is derived from household surveys, including labour force surveys. Some countries, however, use “official estimates” or population censuses as the source of their employment figures. The Employment to Population Ratio is calculated as the number of employed persons of working age divided by total population of working age. Status In Employment

This indicator provides information on the distribution of the workforce by status in employment and can be used to answer questions such as what proportion of employed persons in a country (a) work for wages or salaries;

(b) run their own enterprises, with or without hired labour; or (c) work without pay within the family unit?
According to the International Classification of Status in Employment (ICSE), the basic criteria used to define the status groups are the types of economic risk that they face in their work, an element of which is the strength of institutional attachment between the person and the job, and the type of authority over establishments and other workers that the job-holder has or will have as an explicit or implicit result of the employment contract. These groups of workers are presented as percentages of the total employed for both sexes and for males and females separately. Information on the subcategories of the self-employed group include self-employed workers with employees (employers), self-employed workers without employees (own-account workers), members of producers’ cooperatives and contributing family workers (also known as unpaid family workers). Breaking down employment information by status in employment provides a statistical basis for describing workers’ behaviour and conditions of work, and for defining an individual’s socio-economic group. A high proportion of wage and salaried workers in a country can signify advanced economic development. If the proportion of own-account workers (self-employed without hired employees) is sizeable, it may be an indication of a large agriculture sector and low growth in the formal economy. Contributing family work is a form of labour – generally unpaid, although compensation might come indirectly in the form of family income – that supports production for the market. It is particularly common among women, especially women in households where other members
engage in self-employment, specifically in running a family business or in farming. Where large shares of workers are contributing family workers, there is likely to be poor development, little job growth, widespread poverty and often a large rural economy. Own-account workers and contributing family workers have a lower likelihood of having formal work arrangements, and are therefore more likely to lack elements associated with decent employment, such as adequate social security and a voice at work. The two statuses together, therefore, are summed to create a classification of “vulnerable employment”, now an indicator of the MDG employment target. Conversely, wage and salaried workers, as well as employers, are more likely to benefit from these elements. International recommendations for the status in employment classification have existed since before 1950.5 In 1958, the United Nations Statistical Commission approved the International Classification by Status in Employment (ICSE). At the 15th International Conference of Labour Statisticians (ICLS) in 1993, the definitions of categories were revised.6 The 1993 revisions retained the existing major categories, but attempted to improve the conceptual basis for the distinctions made and the basic difference between wage employment and self- employment. The 1993 ICSE categories and extracts from their definitions follow: * Employees are all those workers who hold the type of jobs defined as “paid employment jobs”, where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work. * Employers are those workers who, working on their own account or with one or a few partners, hold the type of jobs defined as a “self-employment jobs” (i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s). * Own-account workers are those workers who, working on their own account or with one or more partners, hold the type of jobs defined as a “self-employment jobs” [see ii above], and have not engaged on a continuous basis any employees to work for them. * Members of producers’ cooperatives are workers who hold “self-employment jobs” in a cooperative producing goods and services. * Contributing family workers are those workers who hold “self-employment jobs” as
own-account workers in a market-oriented establishment operated by a related person living in the same household. * Workers not classifiable by status include those for whom insufficient relevant information is available, and/or who cannot be included in any of the preceding categories. The status-in-employment indicator presents all six groups used in the ICSE definitions. The two major groups – self-employed and employees – cover the two broad types of status in employment. The remaining four – employers; own-account workers; members of producers’ cooperatives; and contributing family workers – are sub-categories of total self-employed. The number in each status category is divided by total employment to arrive at the percentages. The “vulnerable employment rate” is calculated as the sum of contributing family workers and own-account workers as a percentage of total employment. The Status In Employment are

* Employers
* Employees
1. Employed Full Time
2. Employed Part Time
3. Outsourcing Contractor
* Own Account Workers
* Unpaid Family Workers
* Unemployed
Employment By Sector
The indicator for employment by sector divides employment into three broad groupings of economic activity: agriculture, industry and services. Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour- intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. Classification into broad groupings may obscure fundamental shifts within industrial patterns. An analysis of the data, however, allows identification of individual industries and services where employment is growing or stagnating. Teamed with information on job vacancies by sector, the more detailed data, viewed over time, should provide a picture of where demand for labour is focused
and, as such, could serve as a guide for policy makers designing skills and training programmes that are aimed to improve the match between labour supply and demand. Finally, the breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Are men and women equally distributed in certain sectors, or is there a concentration of females among the services sector? Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment.

International Standard Industrial Classification of all Economic Activities

Revision 2, 1968 – Major divisions
0 Activities not adequately defined
1 Agriculture, hunting, forestry and fishing
2 Mining and quarrying
3 Manufacturing
4 Electricity, gas and water
5 Construction
6 Wholesale and retail trade and restaurants and hotels
7 Transport, storage and communication
8 Financing, insurance, real estate and business services
9 Community, social and personal services

Revision 3, 1990 – Tabulation categories1
A Agriculture, hunting and forestry
B Fishing
C Mining and quarrying
D Manufacturing
E Electricity, gas and water supply
F Construction
G Wholesale and retail trade; repair of motor vehicles, motorcycles and personal and household goods H Hotels and restaurants
I Transport, storage and communications
J Financial intermediation
K Real estate, renting and business activities
L Public administration and defence; compulsory social security M Education
N Health and social work
O Other community, social and personal services activities
P Private households with employed persons
Q Extra-territorial organizations and bodies
X Not classifiable by economic activity

Revision 4, 2008
Revision 4 of ISIC was adopted in August 2008 by the United Nations Statistical Commission and countries were expected to begin reporting data accordingly in 2009. The revision’s objectives are to enhance its relevance and comparability with other standard classifications used around the world, while ensuring its continuity. ISIC Revision 4 incorporates new economic production structures and activities. Moreover, the structure differs significantly from ISIC Revision 3 in order to better reflect current economic organization throughout the world. Meanwhile, the proposed classification structure allows for improved comparison with other standards, such as the Classification of Economic Activities in the European Community (NACE), North American Industry Classification System (NAICS) and Australian and New Zealand Standard Industrial Classification (ANZSIC). Specifically, a comprehensive alignment has been retained with NACE at all levels of the classification, while clear links with NAICS and ANZSIC have been developed at the two-digit level.

Tabulation categories:
A Agriculture, forestry and fishing
B Mining and quarrying
C Manufacturing
D Electricity, gas, steam and air conditioning supply
E Water supply; sewerage, waste management and remediation activities F Construction
G Wholesale and retail trade; repair of motor vehicles and motorcycles H Transportation and storage
I Accommodation and food service activities
J Information and communication
K Financial and insurance activities
L Real estate activities
M Professional, scientific and technical activities
N Administrative and support service activities
O Public administration and defence; compulsory social security P Education
Q Human health and social work activities
R Arts, entertainment and recreation
S Other service activities
T Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use U Activities of extraterritorial organizations and bodies
Full details on the latest revision and links to crosswalks between previous revisions are available at http://unstats.un.org/unsd/cr/registry/isic-4.asp. Hours Of Work
Statistics on the percentage of persons in employment by hours worked per week are mostly calculated on the basis of information on employment by usual-hour bands provided primarily by household-based surveys which cover all persons in employment. In all cases, persons totally absent from work during the reference week are excluded. Annual hours of work are estimated from the results of both household and establishment surveys. For the most part, coverage comprises paid- employment and self-employment. Two measurements related to working time are included in KILM 7 in order to give an overall picture of the time that the employed throughout the world devote to work activities. The first measure relates to the hours that employed persons work per week while the second measure is the average annual hours actually worked per person. The statistics in both tables are presented separately for men and women whenever possible, and devide by age group (total, youth and adult) and employment status (total, wage and salaried workers and self-employed). Unemployment

The unemployed are classified into two that is the actively unemployed and inactively unemployed. The actively unemployed include all persons who did not work during the reference week but were available for work and actively
looking for work during the reference week. Inactively unemployed persons include the following categories: 4. Persons who did not work because they believed no work was available or that they were not qualified; 5. Persons who would have looked for work if they had not been temporarily ill or had it not been for bad weather; 6. Persons who were waiting for result of job applications; and 7. Persons who had looked for work prior to the reference week. To obtain the breakdown of Active and Inactive Unemployment, reasons for unemployment need to be determined for unemployed persons. Youth Unemployment

The four measurements of youth unemployment are:
1. Youth unemployment rate (youth unemployment as a percentage of the youth labour force); 2. Ratio of the youth unemployment rate to the adult unemployment rate; 3. Youth unemployment as a proportion of total unemployment; and 4. Youth unemployment as a proportion of the youth population. Youth refers to those who are between 15 to 24 years age group (in completed years at last birthday) during the reference week. Adult refers to those who are between 25 to 64 years age group (in completed years at last birthday) during the reference week. To obtain the Youth Unemployment number, a breakdown of unemployment and population by age is required. Long Term Unemployment

Long-term unemployment is all unemployed persons with continuous periods of unemployment extending for a year or longer (52 weeks and over); it is expressed as a percentage of the overall labour force (long term unemployment rate) or of total unemployment (incidence of long-term unemployment). To obtain the Long Term Unemployment figure, the duration of unemployment need to be known. Time Related Underemployment

Long-term unemployment is all unemployed persons with continuous periods of unemployment extending for a year or longer (52 weeks and over); it is expressed as a percentage of the overall labour force (long term unemployment rate) or of total unemployment (incidence of long-term unemployment). Inactive Rate

Individuals are considered to be outside the labour force, or inactive, if they are neither employed nor unemployed, that is, not actively seeking work. The inactivity rate is the proportion of the working- age population that is not in the labour force. To obtain the Inactive Rate, the reason for unemployment need to be known. Educational Attainment and Literacy

KILM 14 reflects the levels and distribution of the knowledge and skills base of the labour force. The indicator includes two measures pertaining to educational level of the labour force, and a third measure estimating illiteracy in the youth and adult population. The indicator covers the educational attainment of both women and men in the entire labour force, and also focuses on the proportion of young labour force (aged 25 to 29 years) having completed tertiary education. Employment In The Informal Sector

The informal economy plays a major role in employment creation, income generation and production in many countries. In countries with high rates of population growth or urbanization, the informal economy tends to absorb most of the growing labour force. Since the informal economy is generally recognized as entailing missing legal identity, poor work conditions, lack of membership in social protection systems, incidence of work related accidents and ailments, and limited freedom of association, generating statistics that count the number of persons in the informal economy broadens the knowledge base concerning the extent and content of policy responses required. This KILM combines two measures of the informal economy: employment in the informal sector, the enterprise-based measure defined in the 15th ICLS, and informal employment, the broader job-based measure recommended in the 17th ICLS. The latter includes both persons employed in informal sector enterprises and persons in informal employment outside the informal sector (employees holding informal jobs) as well as contributing family workers in formal or informal sector enterprises and own-account workers engaged in the production of goods for own end use by their household. Informal employment and its subcategories are presented as a share of total non-agricultural employment. Part-Time Workers

The indicator on part-time workers focuses on individuals whose working hours
total less than “full time”, as a proportion of total employment. The ILO defined “part-time worker” as “an employed person whose normal hours of work are less than those of comparable full-time workers”. Thus, the demarcation point is left to the individual countries to define.. Two measures are calculated for this indicator: total part-time employment as a proportion of total employment, sometimes referred to as the “part-time employment rate”; and the percentage of the part- time workforce comprised of women. To compute this indicator, the length of working hours and the breakdown of employment by gender is required. Poverty, Working Poverty And Income Distribution

Poverty can result when individuals are unable to generate sufficient income from their labour to maintain a minimum standard of living. The extent of poverty, therefore, can be viewed as an outcome of the functioning of labour markets. Because labour is often the most significant, if not the only, asset of individuals in poverty, the most effective way to improve the level of welfare is to increase employment opportunities and labour productivity through education and training. Labour Productivity

Productivity, in combination with hourly compensation costs, can be used to assess the international competitiveness of a labour market. Economic growth in a country or sector can be ascribed either to increased employment or to more effective work by those who are employed. Labour productivity is defined as output per unit of labour input, therefore, is a key measure of economic performance. An understanding of the driving forces behind it, in particular the accumulation of machinery and equipment, improvements in organization as well as physical and institutional infrastructures, improved health and skills of workers (“human capital”) and the generation of new technology, is important in formulating policies to support economic growth. Dimensional Analysis Of Labour Market Indicators

The parameters for analysing the Labour Market Indicators are linked to their relevant indicators in section 8. In this section, the parameters are described in more detail. Geographical Location
Analysis by locations are to be sub-categorized into
* Regions (North, Central, South, East Coast, Sabah, Sarawak) * States
* Townships
* Urban/ Rural stratums
Industrial Sectors
Analyses by industrial sectors shall follow the Malaysian Standard of Industry Classification Malaysian Standard Industrial Classification
The Malaysian Standard Industrial Classification is a classification scheme for all economic activities in Malaysia. It was developed based on the International Standard Industrial Classification of All Economics (ISIC) Revision 4 which was released in December 2006. It is a classification scheme for economic activities, not products, services or occupations. At the highest level, economic activities are categorized into 21 sections, which are * Agriculture, forestry and fishing

* Mining and quarrying
* Manufacturing
* Electricity, gas, steam and air-conditioning supply
* Water supply; sewerage, waste management and remediation activitie * Construction
* Services
* Wholesale and retail trade; repair of motor vehicles and motorcycles * Transportation and Storage
* Accommodation and Food Service Activities
* Information and communications
* Financial and Insurance/Takaful Activities
* Real Estate Activities
* Professional, Scientific and Technical Activities
* Administrative and Support Services Activities
* Public Administration and Defence; Compulsory Social Security * Education
* Human Health and Social Work Activities
* Arts, Entertainment and Recreational
* Other Service Activities
* Activities of Households As Employers
* Activities of Extraterritorial Organisations and Bodies Each section is
broken down into further fine-grained levels * Section
* Division
* Group
* Class
* Item
Types of Business Ownership
The types of business ownerships is categorized into
* Private Limited Company
* Partnership
* Co-operative
* Association
* Sole Proprietorship
* Organization
* NGO
* Public Limited Company
* Not Stated
Types of Equity Ownership
The types of equity ownership are categorized as follows
* Local
1. Bumiputera
2. Non-Bumi
3. Bumi/Non-Bumi Partnership
* Foreign
* Local/ Foreign JV
Equity Size
This will be based on bands of Paid-Up Capital of the employers Workforce Size
This will be based on bands of the size of workforce employed by the employer Employment Types
This consists of
* Direct Recruitment
* Outsourcing
* Part-Time
Compensation Components
These are analyzed into non-mutually exclusive categories
* Share of Profit
* Salary
* Bonus
* Incentives
* Attendance Incentives
* Commissions
* Service Charges
* Allowances & Types
Compensation Practices
These are analyzed into the following non-mutually exclusive categories * Rate Systems
* Employment Benefits
* Promotion
* Increment
* Incentives
* Allowances
Country of Origin
The country of origin is used to analyzed foreign labour and sources of investment, and are categorized into * Local
* Foreign
Gender
Gender is categorized into
* Male
* Female
Ethnicity
Ethnicity is categorized into
* Malaysian citizens
* Bumiputera
* Malay
* Other Bumiputera
* Chinese
* Indian
* Others
* Non Malaysian citizens
Education Attainment
Education attainment is used to categorize existing labour, demand for labour
(historical and projected) and supply of labour (historical and projected), and is categorized into * No formal education

* Primary
* Secondary
* Tertiary
These are further sub-categorized into Highest Certificate Obtained categories as follows * UPSR/UPSRA or equivalent
* PMR/SRP/LCE/SRA or equivalent
* SPM or equivalent
* Degree, diploma, certificate, STPM or equivalent
* STPM or equivalent
* Certificate
* Diploma
* Degree
* No certificate
* Not applicable
Years of Employment
These are categorized into bands representing years of being employed Age Groups
These represents age bands for the employees
Employment Status
These represent the status of employment categorized as follows * Employers
* Employees
* Employed Fulltime
* Employed Part Time
* Outsourcing Contractor
* Own Account Workers
* Unpaid Family Workers
* Unemployed
Skill/ Discipline Types
These are categories of training areas as categorized by the Ministry of Higher Education Soft Skill Types
The soft skills possessed and required by labour are categorized into * Communication & Inter-Personal
* Information Technology
* Finance & Account
* Sales & Marketing
* Management & Administration
* Technical Skills
* Literacy
* Others
Special Groups
Special focus groups of labour are categoried into
* Aborigines
* Disabled
* Ex-Drug Addicts
* Ex-Prisoners
* Public Service Pensioners
* Youths
Activities carried out during un/under-employment
The types of activities carried out during periods of under-employment or unemployment are standardised as (non-mutually exclusive) * studying
* just completed schooling
* being a housewife
* loss of capacity to work
* retired
* out of seasonal work
* temporary lay-off
Reasons for unemployment
The reasons for unemployment are standardized as follows (non-mutually exclusive) * schooling/ studying
* being a housewife
* no suitable job
* bad weather
* illness, childbirth or abortion
* awaiting job appointment
* awaiting further studies
* incapacitated
* not interested
* awaiting results of job applications
* no suitable qualification
* retired
* others
Data Quality Assessment
In this section, the survey, census and administrative data sources are analyzed and reviewed for suitability to satisfy the needs of the Labour Market Information Indicators and Statistics. Methodology

The methodology employed in this study for the purpose of evaluating the quality of available data is based on the six dimensions of Canadian Data Quality Assurance Framework (Statistics Canada 2002) used in selective combination with other data quality frameworks employed by the European Statistics Code of Practice (2005), Data Quality Framework (Australian Bureau of Statistics, 2009) and OECD countries. The steps involved in the methodology are as follows:

The quality of data is assessed in 6 dimensions. These dimensions are * Relevance
* Accuracy
* Timeliness
* Acessibility
* Interpretability
* Coherence
The dimensions are furher described and elaborated below.
Agencies (Data Sources)
The agencies selected as data sources for this exercise are
* Ministry of Human Resources
* Manpower Department
* SOCSO
* Department of Statistics
* Economic Planning Unit, Prime Minister’s Department
Filteration
During the filtration stage, the quality of data from the data sources are assessed along six dimensions. These dimensions are Relevancy
The first dimension of quality in the framework is Relevancy. This dimension refers to how well the statistical product or release meets the needs of users in terms of the concept(s) measured, and the population(s) represented. Consideration of the relevance associated with a statistical product is important as it enables an assessment of whether the product addresses the issues most important to policy-makers, researchers and to the broader Malaysian community.

The dimension of Relevancy will be evaluated by considering the following key aspects: * Scope and coverage: the purpose or aim for collecting the information, including identification of the target population, discussion of whom the data represent, who is excluded and whether there are any impacts or biases caused by exclusion of particular people, areas or groups. * Reference period: this refers to the period for which the data were, as well as whether there were any exceptions to the collection period (e.g., delays in receipt of data, changes to field collection processes due to natural disasters). * Geographic detail: information about the level of geographical detail available for the data (e.g., postcode area, Statistical Local Area) and the actual geographic regions for which data are available. * Main outputs/ data items: whether the data measures the concepts meant to be measured for its intended uses. * Classifications and statistical standards: the extent to which the classifications and standards used reflect the target concepts to be measured or the population of interest. * Type of estimates available: this refers to the nature of the statistics produced, which could be index numbers, trend estimates, seasonally adjusted data, or original unadjusted data. * Other cautions: information about any other relevant issue or caution that should be exercised in the use of the data. Accuracy

The second dimension of quality in the framework is Accuracy. Accuracy refers to the degree to which the data correctly describe the phenomenon they were designed to measure. This is an important component of quality as it relates to how well the data portray reality, which has clear implications for how useful and meaningful the data will be for interpretation or further analysis. In particular, when using administrative data, it is important to
remember that statistical outputs for analysis are generally not the primary reason for the collection of the data.

Accuracy should be assessed in terms of the major sources of errors that potentially cause inaccuracy. Any factors which could impact on the validity of the information for users should be described in quality statements. The dimension of Accuracy will be evaluated by considering a number of key aspects: * Coverage error: this occurs when a unit in the sample is incorrectly excluded or included, or is duplicated in the sample (e.g., a field interviewer omits to interview a set of households or people in a household). Coverage of the statistical measures could be assessed by comparing the population included for the data collection to the target population. * Sample error: where sampling is used, the impact of sample error can be assessed using information about the total sample size and the size of the sample in key output levels (e.g., number of sample units in a particular geographical area), the sampling error of the key measures, and the extent to which there are changes or deficiencies in the sample which could impact on accuracy. * Non-response error: this refers to incomplete information provided by a respondent (e.g., when some data are missing, or the respondent has not answered all questions or provided all required information). Assessment should be based on non- response rates, or percentages of estimates imputed, and any statistical corrections or adjustment made to the estimates to address the bias from missing data. * Response error: this refers to a type of error caused by respondents intentionally or accidentally providing inaccurate responses, or incomplete responses, during the provision of data. This occurs not only in statistical surveys, but also in administrative data collection where forms, or concepts on forms, are not well understood by respondents. Respondent errors are usually gauged by comparison with alternative sources of data and follow- up procedures. * Other sources of errors: Any other serious accuracy problems with the statistics should be considered. These may include errors caused by incorrect processing of data (e.g. erroneous data entry or recognition), alterations made to the data to ensure the confidentiality of the respondents (e.g. by adding “noise” to the data), rounding errors involved during collection, processing or dissemination, and other quality
assurance processes. * Revisions to data: the extent to which the data are subject to revision or correction, in light of new information or following rectification of errors in processing or estimation, and the time frame in which revisions are produced. Timeliness

Timeliness is the third dimension of quality in the framework. Timeliness refers to the delay between the reference period (to which the data pertain) and the date at which the data become available; and the delay between the advertised date and the date at which the data become available (i.e., the actual release date). These aspects are important considerations in assessing quality, as lengthy delays between the reference period and data availability, or between advertised and actual release dates, can have implications for the currency or reliability of the data.

The dimension of Timeliness will be evaluated by considering two key aspects: * Timing: this refers to the time lag between the reference period and when the data actually become available (including the time lag between the advertised date for release and the actual date of release). * Frequency of survey: this refers to whether the survey or data collection was conducted on a one-off basis, or whether it is expected to be ongoing. If it is expected to be on-going, frequency also includes information about the proposed frequency of repeated collections and when data will be released for subsequent reference periods. Acessibility

Accessibility is the fourth dimension of quality in the framework. Accessibility refers to the ease of access to data by users, including the ease with which the existence of information can be ascertained, as well as the suitability of the form or medium through which information can be accessed. The cost of the information may also represent an aspect of accessibility for some users. Accessibility is a key component of quality as it relates directly to the capacity of users to identify the availability of relevant information, and then to access it in a convenient and suitable manner.

The Accessibility of a statistical collection, product or release will be
evaluated by considering two key aspects: * Accessibility to the public: the extent to which the data are publicly available, or the level of access restrictions. Additionally, special data services may include the availability of special or non- standard groupings of data items or outputs, if required. * Data products available: this refers to the specific products available (e.g., publications, spread sheets), the formats of these products, their cost, and the available data items which they contain. Coherence

The fifth dimension of quality in the framework is Coherence. Coherence refers to the internal consistency of a statistical collection, product or release, as well as its comparability with other sources of information, within a broad analytical framework and over time. The use of standard concepts, classifications and target populations promotes coherence, as does the use of common methodology across surveys. Coherence is an important component of quality as it provides an indication of whether the dataset can be usefully compared with other sources to enable data compilation and comparison. It is important to note that coherence does not necessarily imply full numerical consistency, rather consistency in methods and collection standards. Quality statements of statistical measures must include a discussion of any factors which would affect the comparability of the data over time.

The Coherence of a statistical collection, product or release will be evaluated by considering a number of key aspects: * Changes to data items: to what extent a long time series of particular data items might be available, or whether significant changes have occurred to the way that data are collected. * Comparison across data items: this refers to the capacity to be able to make meaningful comparisons across multiple data items within the same collection. The ability to make comparisons may be affected if there have been significant changes in collection, processing or estimation methodology which might have occurred across multiple items within a collection. * Comparison with previous releases: the extent to which there have been significant changes in collection, processing or estimation methodology in this release compared with previous releases, or
any ‘real world’ events which have impacted on the data since the previous release. * Comparison with other products available: this refers to whether there are any other data sources with which a particular series has been compared, and whether these two sources tell the same story. This aspect may also include identification of any other key data sources with which the data cannot be compared, and the reasons for this, such as differences in scope or definitions. Intepretability

Interpretability is the sixth dimension of quality in framework. Interpretability refers to the availability of information to help provide insight into the data. Information available which could assist interpretation may include the variables used, the availability of metadata, including concepts, classifications, and measures of accuracy. Interpretability is an important component of quality as it enables the information to be understood and utilised appropriately. The Interpretability of a statistical collection, product or release will be evaluated by considering two key aspects: * Presentation of the information: the form of presentation and the use of analytical summaries to help draw out the key message of the data * Availability of information regarding the data: the availability of key material to support correct interpretation, such as concepts, sources and methods; manuals and user guides; and measures of accuracy of data. Findings

Following are our assessment of the quality of administrative and survey/ census data covered within the scope of this study and their suitability for use in providing Labour Market Information Indicators and Statistics Ministry of Human Resources

Data sources in the Ministry of Human Resources covered by the scope of this study are * SOCSO
* Manpower Department
* JobsMalaysia Portal
* National Employment Returns
* Others
* Registration of Vacancies from Employment Agencies *
Registration of Applicants for Employment
* Registration of Job Applicants from Disabled
* Registration of Employers for the Disabled
In this section we evaluate each of these data sources against the data quality assessment criteria employed for the study, to determine the quality and appropriateness of data from these sources for fulfilling the needs of Labour Market Information Indicators and Statistics. SOCSO

SOCSO provides sources of administrative data in 4 different categories, which are * Data on Employers
* Data on Employees
* Data on Contributions
* Data on Claims

The administrative data from SOCSO is collected through the
* Employee registration process
* Employer registration process
* Monthly contribution process
* Claims process

The collection of data by SOCSO is governed by the Employees’ Social Security Act, 1969 and the Employees’ Social Security (General) Regulations 1971. Under these purviews, employers and employee data collection is governed by legal requirements pertaining to the above-mentioned processes. This provides an assurance regarding the accuracy and timeliness of data collected.

Nevertheless, SOCSO does not cover the following categories of persons and as such does not represent the entire population of workers in the market: * A person whose wages exceed RM3,000 a month and has never been covered before. * Government employees.

* Domestic servants employed to work in a private dwelling house which includes a cook, gardeners, house servants, watchman, washer woman and driver. * Employees who have attained the age of 55 only for purposes of
invalidity but if they continue to work they should be covered under the Employment Injuries Scheme. * Self-employed persons.

* Foreign workers.

For the purpose of SOCSO contributions, wages means all remuneration payable in money to an employee. The following payments are considered as wages : * salary
* overtime payment
* commissions and service charge
* payment for leave, sick, annual, rest day, public holidays, maternity and others * allowances, shift, incentive, housing, food, cost of living and others. * Payments made to an employee paid at an hourly rate, daily rate, weekly rate, task or piece rate are also considered as wages.

However, the following payments are not considered as wages : * payments by an employer to any statutory fund for employees * mileage claims
* gratuity payments or payments for dismissal or retrenchment * annual bonus.

Employers are required to fill Employer Registration Form 1 and Employee Registration Form 2 for registration with SOCSO. Employer must fill both forms neatly providing complete details in a legible manner. A copy of the trading, business or company license has to be enclosed.

The name of an employee has to be as per Identity Card. Both the new and old Identity Card numbers of the employee have to be entered. Thereafter, the duly filled forms and relevant documents should be sent to the SOCSO local Office which will then issue the employer with an employer’s Code Number within 1 month. This number will be used in all correspondence with SOCSO.

Contributions should be made from the first month an employee is employed.

Contributions can be made through appointed banks or through post offices in Sabah and Sarawak only. The detail records of contributions to SOCSO can be
sent using * Computer tapes and diskettes

* Electronic data transfers
* Preprinted Form 8A

Administrative data relevant for analysis of Labour Market Information that can be obtained from SOCSO are SOCSO Employer Registration Form
Data from employers is obtained from the Employer Registration Form (Form 1).

The data that is available from these forms are detailed in nature as they contain the record of individual employers. These can be identified by the Company or Business Registration number on the form. The employers’ name and address are also registered, as well as contact details such as telephone number and fax number.

Since all employers are required to be registered with SOCSO, this is a comprehensive set representing the entire population of employers. Furthermore, since the employers are required to update their data as their status change, these data are kept current.

The attributes collected from employers are as follows
* Name of employer
* Company/ business registration number
* Address of employer
* Town (free text)
* Postcode (no State field)
* Telephone/ fax numbers
* e-mail address
* Year of registration
* Year of operation
* Type of ownership (sole proprietor/ partnership/ private limited company/ limited company/ others) * Type of industry (free text)
* Address of business location
* Date of first employee appointment
* Number of employees hired (cumulative to date of registration) *
Salaries paid during month of registration
* Name, NRIC, address of owner/ managing director/ partner (combined free text)

The Address of the employer is a free text field, but the Postcode and Town data allows the State to be determined if it is not included in the Address.

The Type of Business data is a free text and does not follow any convention, in particular the MSIC.

The Type of Ownership data conforms partially to the categorization required, but does not provide breakdown of the Others category into these further sub-classes * Co-operative
* Association
* Organization
* NGO

The relevant data that is available through the Employer Registration process at SOCSO is limited to this set. Relevancy
Since employers are required by law to be registered with SOCSO, the incidents of employers not registering with SOCSO is low. As such, the detailed data collected on registered employers is a fairly good representative of the population of employers. Furthermore, since employers are required to update their information with SOCSO as changes occur, the administrative data from SOCSO is expected to closely reflect the current updated situation. However, not all employers as defined for the purpose of the Labour Market Indicators are registerable under SOCSO. This gives rise to a mismatch of employers not registered under SOCSO but required to be included under the Labour Market Information. These include persons who are * The Self-employed, such as car wash operators, self-employed salesmen, etc * Persons employing family members and daily-rated workers such as food stall operators, etc Only a limited number of employer attributes required for the Labour Market Information can be obtained from SOCSO. These are mapped in Appendix 2 and are limited to * Company Registration Number

* Name of Company
* Town
* Postcode
* State (to be inferred from Postcode and Town)
Type of Ownership can partially be mapped because of its partial conformance with the categorizations required. However Type of Business which is provided as a free text need to be coded into the MSIC industry classification. Accuracy

Employer data collected from SOCSO is expected to have a high degree of accuracy due to its legal requirements. Timeliness
Employers are legally required to register and update their data with SOCSO, and these can be carried out as and when changes necessitate those updates i.e..the data is not subjected to yearly or bi- annual collection processes as happen in surveys. As such these data is expected to have a high degree of timeliness. Acessibility

SOCSO has existing an online system for its database, as such the accessibility to these data should be high. Coherence
There data from SOCSO can be compared for coherence with detailed data about companies from other sources, such as National Employment Return, using the business registration number as the identifier. As such the coherency of the data can be verified Intepretability

Only a limited number of attributes from the employer data from SOCSO can be mapped against the required fields for Labour Market Information. As such, there is a limited degree of interpretability. The available attributes are mapped against the required attributes in Appendix 2. SOCSO Employee Registration Form

Data on employees is collected through the Employee Registration Form 2. They consist of * Name of employee
* NRIC number
* Date of birth
* Gender
* Ethnicity
* Date of employment
* Occupation (free text)
* Employer SOCSO Code
The data on employees kept by SOCSO is on a detailed level i.e. the data is kept on individual employees. The NRIC number serves as an identifier for each employee. Employees earning RM3,000 and less a month are required by law to register with SOCSO, as such it gives a comprehensive representation of a strata of the population of employees i.e.. those earning RM3,000 and less. Employees earning more than RM3,000 a month may be registered and contribute to SOCSO on a voluntary basis. However, it is a common practice for employers to provide insurance coverage from commercial insurance companies for these employees. Although SOCSO requires all employers whose salaries has increased beyond the RM3,000 to continue contributing, it is also common practice that when such employees change their employers, the contributions are discontinued at the new employers. Since employees need to be registered the moment they are employed, the data is kept current by the practice. Relevancy

Since only employees who meet the criteria are required to contribute to SOCSO, the administrative data represented by employees registered with SOCSO does not represent the complete population of employees. It only represents employees who fall under the class required to contribute to SOCSO. However, being a mandatory contribution scheme under law, employee registration and monthly contributions are commonly adhered to by employers. As such the data collected is a good representation of the contributing employees population. class of contributor employees are well represented by the data collected. Additionally, within the broader definition of labour, not every worker falls within the class of employees who are registered with SOCSO. Thus, administrative data from SOCSO cannot provide data on these workers. The employee data that can be mapped from SOCSO to the Labour Market Information requirement are * Name of employee

* NRIC number
* Age band – from Date of birth
* Gender
* Ethnicity
* Date of employment
Since occupation is a free text, it has to be coded into the MASCO classification scheme to conform with the standard used by the Labour Market Information Accuracy
Since employers are bound by law to register and update their employee data with SOCSO (for those qualified under the rules) these data are expected to have a high degree of accuracy Timeliness
Since employers are required by law to register their employees (those who qualify under the rules), these data are expected to be up to date. Acessibility
SOCSO has an existing on line system so the ability to access these data should be high. Coherence
SOCSO keeps detailed employee identified by their NRIC number. These can be checked for coherence against data from other sources such as JobsMalaysia that has similar details. Intepretability
Data from SOCSO contains a limited number of attributes required by the Labour Market Information, thus there is a limited degree of interpretability. SOCSO Monthly Contribution Form
Data on employee contribution serves 2 purposes. Firstly, it serves to identify the level of remuneration that the employee is getting, and secondly, it serves to confirm that the employee remains under the employment of the employer he is registered under. Contribution data is collected from SOCSO Monthly Contribution Form 8A, and consists of the following * Contribution month and year

* Payment type (cheque number/ cash)
* Employer code
* Employer name
* Employer address
* Employee name
* Employee NRIC number
* Employee date start/stop work
* Amount of contribution (no Salary field)
Since contributions are made monthly, the data is kept current with each submission. The Contribution Year and Contribution Month fields serves to identify the month and year that the data is associated with. It is thus possible to maintain a history of the movements and changes in the employee’s status from this field. Since contributions are mandatory, the employment status of an employee with a particular employer can be confirmed through the continuation of contributions. The linkage from employees to employers allow them to be categorized and classified e.g. by sectors of industry. Data on salaries and wages are not collected as part of the data on contributions. However, since the amount of contribution is based on the monthly salaries/wages of the employee, an estimate of the employee’s monthly salaries/wages can be calculated from the amount of contribution. This provides an estimation of the salaries and wages of the employee, but does not provide the exact amount since the determination of contribution amount is dependent on salary bands. Relevancy

SOCSO contributions are made only by a cross-section of the total workers population in the country. Of these, the data collected that can be mapped to Labour Market Information requirements are presented in Appendix 2 and are as follows * Contribution month and year

* Employer – from Employer code
* Employer name
Other data for employer can be linked from the employers’ records using the code above * Employee name
* Employee NRIC number
* Employment status – inferred from employee date start/stop work * Wages – inferred from amount of contribution
Accuracy
SOCSO contributions are mandatory by law and the calculations are based on salaries and wages paid. Due to the legal requirements, the data collected is expected to have a high degree of accuracy. However, current month salaries and wages data are not collected as part of the data. These will need to be estimated via inference from the reverse calculaion of the amount of contribution. Timeliness

For qualified employees, SOCSO contributions are made monthly by employers under law and as such the data should be current. Acessibility
SOCSO operates under an on-line system as such the data should be accessible. Coherence
There contribution data from SOCSO is in detail by individual employee using the NRIC of the employee as key identifier. The salaries and wages amount, albeit having to be inferred from the contribution amount, can be checked as an estimate for reasonable variation against another rdata source with similar details. Another data source that can offer similar details, for example is the Employee Provident Fund (EPF) but it is not covered within the scope of this study. Intepretability

The contributions data provide an estimate of the salaries and wages of each individual employee. For estimation purposes, e.g..determining the salary band of employees, the data, when linked to other employee and employer registration data, provides a certain degree of interpretability subject to the constraints mention for employee and employer data above. Information on the SOCSO member/insured person (claims & benefits) Some Labour Information Information mau be obtained from Claims data. However, since claim data is only available when a SOCSO contributor makes a claim, they represent only a fragment of the entire labour market. For that reason, Labour Market Information from claims data cannot be used to comprehensively represent Labour Market Information. However, information from claims data may be used to in collaboration with employee registration data to provide additional assurance on their basic accuracy. Relevant data collected from various claim forms are * Name of insured/employee

* NRIC number
* SOCSO number
* Date of accident/death
* Death certificate number
Relevancy
Since claims data is only collected for employees who make claims, they represent only a small fraction of the labour population. As such, it ihas
low relevance for representing Labour Market Information. Accuracy

Claims data, backed by employee registration and monthly contribution data, provides a high degree of accuracy on an individual employee level. However, since claims data represents only a samll fragment of the entire population of the labour market, it is not accurate on the aggregate level. Timeliness

Claims data is obtained after the event giving rise to the claim e.g.. death or injury, wherelse the claims data represent the status of the employee at the time of incident. As such a slight delay is expected in the collection of claims data. Acessibility

Since SOCSO operates in a computerised environment, claims data is expected to be easily available. Coherence
The value of claims data is only to collaborate and support other employee data within the system. For example, the existence of the employee as a worker in the population can be determined from both the cessation of contributions from the worker and a claim of death benefits for the same worker. Similarly, registration of a a disabld worker with the Manpower Department may be confirmed by the submission of a disabilities claims from SOCSO. However, for the second example, not all disabled worker will be supported by SOCSO claims, for example for those suffering from disability from birth. Intepretability

There is a limited number of attributes that can be used for Labour Market Information from the claims data. As such the degree of interpretability is low. Manpower Department (JTK)
The Manpower Department owns several major data sources that can be tapped to fulfil the needs of Labour Market Information and Statistics. These sources are * The JobsMalaysia Portal
* The National Employment Returns
* Other Administrative Data Sources
* Registration of Vacancies from Employment Agencies
* Registration of Applicants for Employment
* Registration of Job Applicants from Disabled
* Registration of Employers for the Disabled
JobsMalaysia Portal
The JobsMalaysia Portal collects detailed data on employees and employers i.e. data on individual employer and employee. Individual employers and employees are identified by the NRIC numbers and business/ registration numbers respectively. JobsMalaysia also collects vacancy and job matching details. These data are collected through the following activities

* Registration of Employers
* Registration of Job Applicants (including students who are bout to enter the Job Market i.e. Final Year Students) * Registration of Vacancies
* Matching of Candidates to Jobs and Job Placements, on weekly, monthly and annual basis * Matching of jobs for applicants from Special Focus Groups * Disabled applicants
* Pensioners
* Youths
* Unemployed graduates
* Ex-convicts
* Ex-drug addicts
Although registration with the JobsMalaysia portal is voluntary, operating as the main mechanism under the Department’s Jobs Services, JobsMalaysia Portal has accumulated a significant amunt of data in it’s database. The Job Services program had achieved over 400,000 placements with 218,000 registered employers and 550,00 actively searching applicants. Since the JobsMalaysia portal collects information from jobseekers and employers having vacancies, it provides data on unemployment and labour shortage situations. At the same time, it provides data on jobs matched shedding insight on the rate of fulfilment of both situations. This is unique to the JobsMalaysia data source as other data sources covered in this survey does not provide such extensive and detailed insight into the labour shortage (vacancies), unemployment and job matching rate as the JobsMalaysia database. The Portal caters for the following types of employers

* Individuals
* Enterprises, Partnerships and Companies
* Associations, Embassies, International Associations
* Government Agencies
Information collected from employers during the registration process are * Registrar of Business/ Registrar of Companies Registration Number * Employer name
* Address
* Postcode
* Territory/ Division
* State
* e-mail address
* Web Address
* Phone and Fax Numbers
* Industry and Sub-Industry
Whether interested or not to hire disabled.
Detailed information collected from applicants/employees during the employee registration process * Name
* NRIC number
* Gender
* Marital status
* Race
* Nationality (for now restricted to Malaysians)
* Current job type (public sector/ private sector/ self-employed/ unemployed) * Address
* Postcode
* State
* District/ Division
* e-mail Address
* Telephone Number
* Mobile Phone Number
* Spoken Languages and Ability Levels (Fluent/ Good)
* Written Languages and Ability Levels
* Class of Driving License
* Other Licenses (e.g.. Scuba Diving)
* Applicant Category
* School/ University Leaver
* Seeking Career Enhancement
* Laid Off Worker
* Ex-Armed/ Police Force
* Ex-Addict
* Ex-Convict
* Pensioner – Private Sector
* Pensioner – Public Sector
* Pensioner – Police
* Disabled – Sight
* Disabled – Speech
* Disabled – Hearing
* Midget
* etc
* Education Level
* Tertiary
* Secondary
* Primary
* No Formal Education
* PMR/ SRP/ LCE Achievement
* Year/ Grade
* Subjects and Grade (maximum 10 only)
* SPM/ MCE/ SPM (V)/ SPVM Achievement
* Year/ Grade
* Subjects and Grade (maximum 10 only)
* Bahasa Oral Test Result (Pass/ Fail)
* STPM/ STP/ HSC Achievement
* Year/ Grade
* Subjects and Grade (maximum 10 only)
* Bahasa Oral Test Result (Pass/ Fail)
* PhD/ Masters/ Degree/ Diploma/ Certificate/ Final Year Student Achievement * Graduation Year
* Qualification Level
* CGPA/ PNGK
* Instution
* Is institution a foreign franchisee
* Field of secialization
* Co-Curriculum Information
* Sports field or Uniform Bodies/ Association/ Club
* Level of achievement (International/ National/ State/ District/ Institution/ School) * Position (President/ Vice-President/ Secretary/ Treasurer/ Committee Member) * Work Experience (one only)

* Company Name
* Address
* Position
* Industry and Sub-Industry
* Last Month Salary
* Relevant Experiences (free text)
* Unrelated Expereinces (free text)
* Year Start
* Year End
* Reason For Leaving

The JobsMalaysia Portal collects the following information on each vacancy * Name of position
* Description of position
* Length of vacancy
* Number of vacancies
* District and State of Vacancy
* Closing date for Applications
* Target Applicant Type (e.g. Pensioner)
* Working Hours (e.g. Normal)
* Offered Salary
* Gender
* Marital Status (e.g. Irrelevant)
* Contact Person, Phone Numbers and Cell Phone (2 persons) * Academic Achievement Level (Tertiary/ Secondary/ Primary/ No Formal Education) * Language Proficiency
* Age Group
* Vehicle Provided By Employer
* Type of Driving License Required
* Type of Professional License required
The name of position vacant is a free text field and it does not adhere to any standard scheme of classification such as MASCO. It provides data for the highest level of education attainment required for the position, but does not solicit specific areas of qualifications. Relevancy

With over 200,000 registered employers and 500,000 job applicants in its database, JobsMalaysia presents a fairly large pool of Labour Market data for analysis. Additionally, the portal provides rich data sets with attributes on detailed data not available from other sources, particular in areas such as job vacancies and unemployment. It’s job placements data also provides a rich data set in terms of the attributes on the nature of of vacancy to determine the rate at which labour supply is taken up by employers. Having accumulated a database with hundreds of thousands of employers, employees, job-seekers, vacancies and job matches, the JobsMalaysia portal provides a rich source of data that can be used for sampling purposes. In lieu of a survey, the JobsData database already contains detailed rich data with attributes that can be stratified, analysed and be used to represent the entire Labour Market population. The data in the JobsMalaysia database changes from time to time depending on what is registered in the portal at the time. As such, where it is used for sampling purposes, it is necessary to determine any skewness in data that may be present during the time of sampling, and whether samples extracted from the database accurately represents the composition of the entire Labour Market. However, since JobsMalaysiaportal works on a voluntary basis, where employers and potential employees register into the portal on a voluntarily, it does not provide a complete data set repersenting the entire Labour Market Information. Data in the JobsMalaysia portal is rich with varieties of attributes. The matching of these attributes against the requirements for Labour Market Information is summarised in Appendix 2. Many of these attributes such as age, gender and marital status, can be used directly to fulfil analytical requirements of the Labour Market Information. However, there are attributes that need to be re-coded to fit into the standardized classification schemes used in the Labour Market Information, for example
classification of occupations (to follow MASCO). The data from JobsMalaysia does not cater for some of the attributes required by the Labour Market Information. The data mapping in Appendix 2 summarizes the situation. Data not provided by JobsMalaysia for example is company ownership category.. Accuracy

Data in the JobsMalaysia portal is provided voluntarily by registrants and is not verified at the database level. For example, a potential job candidate can claim to possess certain certifications while entering his/her registration. However, this data is provided in expectation that it shall be used during a job appointment stage, wherein the certifications provided by the candidate is checked against the certificates that he can produce. As such, the data is expected to have a high degree of accuracy from that point of view. The completeness of data in the JobsMalaysia database, however, cannot be ascertained on the basis of the database alone, as registration is on a voluntary basis. Furthermore, updates into the datbase is also done on a voluntary basis. For example, unemployed job candidates that were looking for jobs at one point in time may have obtained a job outside the JobsMalaysia portal. The appointment is not updated into the portal and the candidate is left in the database as a candidate looking for a job as an unemployed. In this sense, the employment status of the candidate cannot be exactly determined from the JobsMalaysia databse alone. Additional data gathering or surveys may need to be carried out to gather additional status updates and ascertain the accuracy of the data over time. Timeliness

Data in the JobsMalaysia database is updated on a voluntary basis. There will be varying degrees of timeliness exercised by the registrants. For example, employers may register a vacancy after several months of futile search outside the JobsMalaysia portal. Another employer may first go to the JobsMalaysia portal to register a vacancy. Similarly. an unemployed job-seeker who ultimately finds a job outside the JobsMalaysian portal may update his employment status immediately, or after some time, or not at all. Campaigns are conducted by the Manpower Department to register employers and job-seekers in job fairs and other events. When these events are held, data in the Jobs Malaysia may be flushed with current updates again. Acessibility

Since the JobsMalaysia portal is managed with an on-line database, the accessibility to the data is considered high. Coherence
Data within the JobSeekers database is controled by key identifiers. For example, for employers, the Registrar of Businessor Registrar of Companies data is used, whilst for job-seekers the NRIC is used. This provides means to ensure that the same employer and employees are not created twice in the database, but updates are entered against existing data. This ensures that data for the same employers and job- seeker remains consistent. The identifier mechanism also provides capability for the data to be cross-verified against detailed data from other sources, for example, SOCSO. As such the degree of coherency of the data is high. Intepretability

Data collected by JobsMalaysia is rich with attributes for all datatypes. Some of the attributes meet the requirements of the Labour Market Information. Many of the attributes are not required for Labour Market Information but but can provide additional dimensions of insight into the Labour Market situation. These provide a high degree of interpretability to the information. As mentioned above, some of the attributes required by the Labour Market Information is not available from the JobsMalaysia database, and a few attributes require re-coding into the standard classification scheme used in the Labour Market Information. National Employment Returns

The National Employment Returns are surveys conducted bi-annually to obtain information on * Employers Profile and Composition
* Employees Profile and Composition
* Wage and Salary Levels
* Remuneration practices
It provides a rich data set on the employment situation in Malaysia, providing details on employers (employers furnish returns by identifying themselves with the Business Registration or Company Registration Numbers). The sampling is based on employers registered with the Labour Market Database (LMD) only employers in the private sector is included and it specifically excludes * public sector organizations

* self-employed persons
* Non-Governmental Organizations (NGOs)
The workforce included in the survey covers
* Local Workers
* Expatriates
* Foreign Workers
Since the furnishing of returns by employers is governed by law, the survey enjoys a good rate of response. The number of samples taken for the 2009 Survey is 31,995 establishments (from 232, 437 employers in the LMD employing 3.35 million workers) out of which 77% responded. The period covered was July to August 2009. This makes the survey a rich source of data for analysis. Furthermore the availability of employer Business or Company Registration number allows the data furnished to be cross-checked against employer data from other sources such as SOCSO and JobsMalaysia. The survey method is a self-administered survey where respondents were sent the survey forms and after filing them themselves, the forms were returned to the Ministry of Human Resources. The unit of analysis is the private sector employers.This method does include a verification of the accuracy of data reported in the survey. This situation may be mitigated by conducting small verification surveys in which data collected through NER is verified for accuracy against administrative data furnished to other agencies, such as SOCSO, EPF or the Registrar of Companies/ Businesses. The levels of confidence in the data can then be determined. However, this implies that the data gathered is used as a basis for surveys. It does not provided for a thorough verification of the enitire data available in the database. In 2009, the skewness in geographically distribution of the samples are 84% samples were from Peninsular Malaysia and 8% each from Sabah and Sarawak. This will differ from time to time and survey to survey. This also highlights different interpretations of skewness from different points of view. Sampling of data is conducted by extracting employers from the database. This may represent a different characteristic of skeneww in terms of employees in the market. For example, in terms of sectoral distribution, 42% of the responding employers are in the distributive trade sector which includes wholesale and retail trade, repair of motor vehicles, motorcycles and personal and household goods. This is not representative of the workers
employed since the sector accounts for only 21% of all employees. By contrast, the manufacturing sector which had only 8% of all employers employed 28% of all employees.” In terms of the distribution of sizes of employers, most who are registered with the LMD are small and medium scale enterprises (SME) with 78% of them employing less than 10 workers and 59% of them having a paid-up capital of less than RM100,000. In terms racial breakdown of ownership, the majority of employers in the LMD are registered as sole-proprietors with 64% of them being owned by non-bumiputeras. The survey is conducted under the provisions of Section 63 of the Employment Act 1955, Section 59 of the Sabah Labour Ordinance (Cap. 67) and Section 60 of the Sarawak Labour Ordinance (Cap. 76) which gives it a legal status and influences respondents to respond to the survey and reply the questionnaires correctly and responsibly. Relevancy

Samples for the National Employment Survey is extracted from the Labour Market Database, which is a skewed representation of employers in the market. For example, the LMD is skewed towards small and medium scale enterprises. As such, the samples extracted and thus the results obtained may be relevant to certain cross-sections of the Labor Market but not for the entire Labour Market. The level of response to the survey is high making it an excellent representation of the market sector that it is skewed for. A rich set of data attributes is collected in the survey amny of which are directly relevant for use in the Labour Market Information. The mapping of attrbutes collected in the survey and those required by Labour Market Information is provided in Appendix 2. Accuracy

The National Employment Return, albeit being a self-administered survey, is conducted under law. As such, respondents are responsible for furnushing accurate data in response to the survey. The data as such, is expected to be high in accuracy. Additional sampling for verification purposes conducted to determine the level of confidence and margins of error in the collected sample data may be conducted. Timeliness

The survey involves a great deal of data collection and consolidation. As such, there is a time lag between the sampling time period and the
publictaion of the data. Additionally, the survey is conducted bi-annually and as such results are only available on a bi-annual basis For this reason thNER as a data source has a low level of timeliness with respect to current Labour Market Conditions. Acessibility

Data for NER is collected in manual forms and is collated with manual intervening processes. As such the degree of acessibility to the data is low, unless an online survey mechanism is set-up to collate the data and process it automatically. Coherence

Since the NER identifies responding employers by their Business or Company Registration Numbers, it is possible to cross-check the data furnished in the NER against data from the same employers elsewhere such as to SOCSO and EPF. This ensures the degree of coherence in the data. Data for employees in the NER is not collected at the detailed level i.e.. employee data is collected as a summary without recording particulars of every employee and identifiyng each worker with an identifier such as IC number. GIven this situation, the coherency of employee data need to be checked on total basis and trends or commonalities be establsihed against data on groups of employers with similar characteristics. For example, common worker salary levels may be determined amongst employers within the same industrial classifications. Intepretability

The data in NER contains a rich set of attributes allowing it to be interpreted from amny angles. Labour Market Database
Relevance
The Labour Market Database provides a rich source of information on the labour market. Although all the information relates to the labour market, not all of the information is relevant for generating the Key Information on Labour Market Indicators. Accuracy

Information in the Labour Market Database is deemed to be accurate as the data is collected under a legalized process and the employers furnishing them are responsible for inaccuracies reported. Timeliness

Data is updated into the Labour Market Database from submissions collected in an ongoing process. Thus, it is deemed to be timely. Accessibility
The data in the Labour Market Database is stored in a database as is easily accessible provided that the security permissions are obtained. Coherence
Data from the Labour Market Database may be crossed checked against each other, as such it is considered coherent. Interpretability
Many of the data items in the Labour Market Database does not conform to the standard reference items that this exercise refers to. As such, to be useful, these non-standard data items need to be reclassified into the standardised categories. Management of Foreign Labour

Relevance
The information on number of foreign workers by employers is relevant as a data source Accuracy
The number of foreign workers reported is expected to be accurate as the application is a legal requirement. However, as no application is required for additional new workers once an application had been approved, data updates need to be obtained from other means and sources. Timeliness

The data is considered to be timely as employers are required to apply before making any salary deduction for health insurance. However, since the data is not updated for additional new workers, updates to the existing data is not available at all. Accessibility

The data is easily accessible as it is kept by the Labour Department. Coherence
The data may lose its coherency with data from other sources if existing new employers were to employer additional new foreign workers, as they are not required to re-apply. Interpretability
Parameters collected in the application do not conform to the required standards (e.g. in Type of Business) and as such need to be re-coded for conformity. Others
Apart from the major sources managed by the Manpower Department i.e. the JobsMalaysia Portal and the National Employment Returns, the Manpower Department also collects data on aspects of the Labour Market through other
minor processes such collection of data from employment agencies and from employers of the handicapped. These data are

* Registration of Vacancies from Employment Agencies
* Registration of Applicants for Employment
* Registration of Job Applicants from Disabled
* Registration of Employers for the Disabled

These data are collected on a detailed level i.e. individual employers and employees are registered through the processes. In terms populaion representation, the registration of handicapped is voluntary and thus it does not guarantee that all handicapped will be in of the data set.Similarly, employers and job candidates registering at employment agencies are on voluntary basis, and there is no assurance that their returns represent the entire population of employers and job seekers. In terms of data accuracy and currency, there is no mechanism to close the status of persons and companies registering through these means. Without closure, the status of the vacancy or job seeker will remain the unchanged in the system although the actual situation has changed in reality. In particular, the following situations are not catered for * Unemployed person registers with employment agents but finds employment through other means * Employers register through employment agents but finds employment through other means * Unemployed person registers with more than one employment agency * Employers register the same vacancy with more than one employment agency Data solicited through forms other than the National Employment Returns contains the following information on employers * Name of employer

* Address
* Telephone/ fax numbers
* Nature of Business
For employers of disabled persons, additional information is collected * Registered address
* Type of industry
The registration of employers does not note down their Registrar of
Businesses or Registrar of Companies’ registration numbers. Relying on the business or company name is insufficient to ensure the identity of employers registered, due to misspelling, duplicate names, etc. Data collected through those means on employees are

* Name
* Address
* Date of Registration
* NRIC No
* Gender
* Qualification and Experience
With the NRIC number, it is possible to identify each individual job seeker. The qualification and experience collected is in the form of free text and not in accordance with any standard classification scheme. Information is collected for applicants who are successfully matched to employment placements * Name of employers

* Address of employers
* Starting salary
* Work position
For disabled persons, additional information is obtained
* Marital status
* Name of Association
* Contact person for association
* Type of disability
* Cause of disability
* Type of support equipment used
* Name of next-of-kin
* Address of next-of-kin
* Allergies (if any)
* Qualifications
* Experience
* Soft Skills
* Status of applicant (seeking employment/ working/ studying/ training/ others) * Salary range requested (per annum)
* Date employment is required
* Type of work seeked
* Location (area/ state) of work requested
* Special facilities requested (transportation/ accommodation/ railings/ toilets/ etc) Data on vacancies are also collected as follows
* Name of Position
* Location of Work
* Job Requirements/ Pre-requisites
* Qualifications and Experience Requirements
* Number of Positions
* Date of Vacancy
The data on vacancies does not adhere to any standardized classification scheme on job requisites, qualifications and experience requirements. Similarly, vacancies for the disabled are not coded for uniformity. For vacancies for the disabled, additional information is collected * Name of positions

* Number of vacancies (by gender and type of disability)
* Minimum salary offered
* Minimum qualifications/ skills/ experience required
* Special amenities provided (transportation/ accomodation/ railings/ toilets/ etc) * Working environment (air-conditioned/ hot air/ dusty/ fans) Relevancy
These other data sources maintained by the Manpower Department is considered low in relevance as they do not represent the represented labour population comprehebsively. Also the format and type of attributes collected is few in numbers not permitting many to mapped against the Labour Market Information requirements. Accuracy

The accuracy of data attributes collected is expected to be high as they are representative of job candidates (in both cases of handicapped and persons registered with employment agencies) whse attributes will be verified during the job interview and selection stage. On the other hand data furnished by employment agencies are not verified and there is a low level of assurance that their data furnished is complete. Timeliness

Data is collected as and when the handicapped register themselves. There is no assurance that the data set is representative of the state of the handicapped workers population at any point of time. Data from employment agencies are collected on aregular basis. Howver, since registration of job-seekers at employment agencies are on an as-and-when basis, the dataset of job-seekers in particular the unemployed may not represent the population of unemployed or job- seekers in the Labour Market at any point in time. As these data is not collected and updated through regular or scheduled submission of returns, the timeliness of the data in representing market conditions is low. Acessibility

Data from handicappd and employment agencies are collected in manual forms and collated into statistics. Without a comprehensive computerised system such as SOCSO or JobsMalaysia, the accessibility to the data is low. Coherence

Data collected on the handicapped may be checked against coherency against other data sources such as disability claims from SOCSO. Howver, not all handicapped may claim from SOCSO. Thus the ability to check for coherency is low. Data on job seekers collected employment agencies imay be cross- checked against each other for coherency in patterns and characteristics of job seekers. Intepretability

A limited number of attributes is collected from these data lending to a medium level of intepretability. Department of Statistics Malaysia
Data sources in the Ministry of Human Resources covered by the scope of this study are * Labour Force and Social Statistics
* Labour Force Survey Malaysia
* Migration Survey
* Wages and Salary Survey
* Labour Force Statistics
* Population and Demography
* National Population and Housing Census
* Household Income
* Business
* Economic Census
* Household Income
In this section we evaluate each of these data sources against the data quality assessment criteria employed for the study, to determine the quality and appropriateness of data from these sources for fulfilling the needs of Labour Market Information Indicators and Statistics. Labour Force And Social Statistics

The Department of Statistics conducts Labour Force Survey, Population Census, Economic Census and Household Income Surveys in which pertinent data on the Labour Market is collected. Labour Force Survey Malaysia

Data for the Labour Force Survey is collected through the same form that is used for the Migration Survey and Wages and Salaries Survey. The unit of data collected is on a per household basis, which is different and complements the data collected for the National Employment Returns, which is on an Employer Establishment basis. Data from the Labour Force Survey is collected on a sampling basis. Although the survey is published annually but the data is collected in monthly surveys. By relying on the monthly input from surveys, it would be possible to produce monthly updates to the Labour Market Information. The personal interview method is employed for the survey. Interviewers visit households in selected areas to collect information. Field checks are carried out to correct errors and omissions. Data collected is not verified with collaborative evidence in this method. All household members will be asked the following information: * relationship to household head

* sex
* age
* ethnic and citizenship
* marital status
* educational attainment
For those aged 15 years and over (who are considered to be workforce age), their activity status – either employed, unemployed or outside labour force
– will be determined. Information collected from the employed include whether they had working or not during the reference week, the number of hours worked, occupation, industry and status in employment, and if they have worked less than 30 hours per week, reasons and willingness to accept additional work. If they have not been working during the reference week but have a job to return to, the reasons for not working would be sought. The following questions will be sought to those who are unemployed: * action taken to look for work

* work experience
* duration of unemployment
Those who are classified outside labour force will be asked to state the reasons for not seeking work and working experience. The Labour Force Survey covers both urban and rural areas of all states in Malaysia. The survey population is defined to cover persons who live in private living quarters and hence exclude persons residing in institutions such as hotels, hostels, hospitals, prisons, boarding houses and military barracks. The survey comprises the economically active and inactive population. To measure the economically active population, the Labour Force Survey uses the age limit of 15 to 64 years. The economically active population comprises those employed and unemployed whereas those who are inactive is classified as outside labour force. The frame used for the Labour Force Survey is from the National Household Sampling Frame (NHSF) which is made up of Enumeration Blocks (EBs) created for the 2000 Population and Housing Census. EBs are geographically contiguous areas of land with identifiable boundaries. On average, each EB contains about 80- 120 living quarters. Generally, all EBs are formed within gazetted boundaries, i.e. within administrative districts, mukim or local authority areas. Information obtained from the survey provides input for analysing the labour market situation, policy formulation as well as planning, implementing and monitoring programmes related to human resource development. Relevancy

Data for the Labour Force Survey is collected on a Household basis. Since households reflect employees, the data represents the employee’s point of view of the statistics. The data is based on samples collected for surveys,
unlike census data it does not cover the entire population but is used to represent the population. As such, in order to represent the entire population, the data need to be extrapolated from the sample to the population. Accuracy

Data for the Labour Force Survey is collected using the personal interview approach. The data is not verified against any documentary evidence and is taken as correct as declared. As such the accuracy of data collected for the Labour Force Survey depends on the accuracy of data provided personally by the respondent. Timeliness

Data for the Labour Force Survey is collected monthly. This provides an updated estimates on the state of the labour market on a monthly basis, suitable to reflect changes in the labour market as they occur. Acessibility

Data for the Labour Force Survey is collected and kept by the Department of Statistics Malaysia. They are published on an annual basis. However, if the survey data can be obtained from the Department of Statistics, then monthly data may be obtained. Coherence

Workers’ and Household data from the Labour Force Survey can be compared between time periods and with employee data from other sources such as SOCSO to determine its coherence Intepretability
The data for Labour Force Survey is rich with dimensions for analysis purposes and as such is may be interpreted in a large number of ways. Migration Survey
The Migration Survey is carried out simultaneously using the same survey form with the Labour Force Survey and covers the same survey population i.e. urban and rural areas for all states in Malaysia. The population covered consists of persons aged one year and over residing in selected private living quarters in Malaysia. The main objective of Migration Survey is to provide estimates of population movements and trends at state level. In addition, this survey also aims to obtain the socio-economic information of migrants and non- migrants such as age, sex, employment and type of occupation at the place of destination. The scope of migration data in the
survey is limited to fixed-term migration. Respondents are asked for the usual place of residence on two specific reference dates which are exactly one year apart. A change in the usual place of residence locality between these two points constitutes migration. Relevancy

The purpose of the Migration Survey is to collect data on migrations between rural- urban and inter-states. It has an indirect relevance to the Labour Force Information Indicators and Statistics in that it provides additional supporting data regarding the movement of workers. However, since the Labour Market Information Indicators and Statistics uses its location attribute to indicate the current location of the worker, this statistics from the Migration Survey does bear directly to the results. This is also taking into account that the current location of workers are collected for the Labour Force Survey, suing the same survey form and sample base as the Migration Survey. Accuracy

Data for the Migration Survey is self-declared and is not verified. As such, the accuracy of data is dependent on the accuracy of the declaration. Timeliness
data collection for the Migration Survey is conducted monthly, the same as the Labour Force Survey. Thus it provides monthly updates to reflect the changing states of the labour market. Acessibility

The data may be made available on a monthly basis by the Department of Statistics Malaysia. Coherence
Data from the Migration Survey can be compared with population growth and declines in various locations, taken from the Population and Housing Census and other sources to confirm its coherence. Intepretability

Collected as part of the Labour Force Survey, the Migration Census collects a rich set of attributes for workers and provides a high degree of interpretability. Wages and Salary Survey
Salaries and Wages Survey is conducted using household approach and is conducted together with the Labour Force Survey using the same survey form Basic wage rate can be obtained from this survey and is used to measure wage
differentials and gender wage gap. Salaries and wages information is only collected from respondents aged 15 and over with the status in employment of either “Government Employee” or “Private Employee”. Relevancy

The wages and salary survey is highly relevant to the Labour Market Information in providing in formation on employee remunerations. However, since the data is collected on a sampling basis, the sample need to be extrapolated to represent the population in order to be used. Accuracy

The Wages and Salary Survey is based on self-declared data, therefore the accuracy of data is dependent on the accuracy of the declaration. It is not verified against documentary evidence such as pay-slips. Timeliness

Data for the Wages and Salary Survey is collected on a monthly basis together with the Labour Force Survey. Thus, the data reflects current market conditions in a closer manner compared to annual statistics. Acessibility

The Department of Statistics may provide the data collected for the survey on a monthly basis. Coherence
Data for the Wages and Salaries Survey may be compared to remunerations statistics derived from other sources such as the National Employment Returns as well as administrative data from SOCSO and JobsMalaysia to determine its coherence. Intepretability

The Wages and Salaries Survey is conducted together with the Labour Force Survey and the Migration Survey which collects a rich variety of attributes for each worker. As such the data is highly interpretable. Labour Force Statistics

The Labour Force Statistics is represented by a time series data obtained from the Labour Force Survey and presented annually since 1982 with the exception of 1991 and 1994 during which the survey was not conducted. The data represents estimations of

* Labour Force
* Distribution of Employment by Occupation and Industry
* Unemployment
Labour Force is taken as those on the age groups between 15-64 years old and includes both employed and unemployed persons. Employed persons are all those who were worked for at least 1 hour during the reference week. It also includes those who have employment but did not work because of injuries, holidays and similar reasons. Unemployed persons are classified into two groups which are * the actively unemployed and

* the inactively unemployed.
The actively unemployed include all persons who did not work during the reference week but were available for work and actively looking for work during the reference week. * The inactively unemployed persons include the following categories: * Did not look for work because they believed no work was available or they were not qualified; * Would have looked for work if they had not been temporarily ill or had it not been for bad weather; * Waiting for answers to job applications; and

* Looked for work prior to the reference week.
In addition to the Labour Statistics time series, the Department of Statistics also publish the following time series data * Total number of paid workers
* Total amount of salaries and wages paid
* Value of gross output
* Cost of input
* Value add
* Value of assets owned
The data is analysed by the following industries
* Mining and quarrying
* Construction
* Services (sub-categorised into sub-services)
* Manufacturing
Relevancy
The labour Force Statistics is highly relevant for the purpose of the Labour Market Information Indicators and Statistics. It provides historical data
constructed into time series showing trends and cycles faced by the Labour Market. Since the data set for the Labour Force Statistics originates from the Labour Force Survey, the assessment on Labour Force Survey applies to the Labour Force Statistics. Accuracy

The Labour Force Statistics derives its time series data from the Labour Force Survey. Since the data for labour Force Survey is collected using the personal interview method, the accuracy of data collected is based on the accuracy of data declared during the interview. Timeliness

The Labour Force Statistics aggregates data on an annual basis. However, since the data is derived from the Labour Force Survey which is collected on a monthly basis, the time series can be broken down into months to cater for monthly updates. This provides monthly trends and cycles from the time series. Acessibility

The data for the Labour Force Statistics may be obtained on a monthly basis from the Labour Force survey data which is collected monthly by the Department of Statistics Malaysia. Coherence
Data for the time series from the Labour Force Statistics can be compared with time series constructed from other data sources, such as SOCSO, to provide a guide on its coherence. Intepretability
The data for The Labour market Statistics, derived from the Labour Force Survey is rich with attributes on workers and their household which can be used for analysis. Therefore, the data from The Labour Force Statistics is highly interpretable. Population and Demography

The Department of Statistics produces the Population and Economic Census every 10 years and from there time series on the population is constructed National Population and Housing Census
The Population and Housing Census is conducted once in every 10 years. The last Census was conducted in 2010. The Census was conducted using face to face interview. Information collected includes the number of persons and households together with a wide range of demographic, social and economic characteristics. Information on housing stock, structural characteristics of
houses as well as amenities in living quarters is collected. The Census data is published in various reports according to special topics which is made available at the Users Service Unit of DOSM. The statistics on housing and population will be used as inputs in the development planning, formulation of policies by the government as well as other users. Additionally quarterly estimates are produced for the following * Population, analysed by gender, ethnic groups and age groups * Population growth i.e. Natural Increase, Birth, Death and Life Expectancies * Employment by Industry and Occupation

Relevancy
Data from The National Population and Housing Census and the quarterly estimates are highly relevant in providing data on the * Population
* Working Age Population
* Population Growth and Life Expectancies
* Employment
However, the data collected is not analysed by a set of attributes that is as rich as the analysis done for the National Employment Returns and the Labour Force Survey. Accuracy
Accuracy of data from the census has been reliably used for various usages and is taken as an accurate estimate of the population. The accuracy of the 10-year census data is supported by the quarterly updates published by the Department of Statistics. Timeliness

The quarterly updated statistics provide a good representative of current market conditions while the 10-year census provide a benchmark every decade. Acessibility
The data may be obtained from the Department of Statistics.
Coherence
Data from the National Population and Housing Census is used as a benchmark in various applications, and its coherence can be verified against the quarterly estimates published by the Department of Statistics. Intepretability

The data from the national Population and Housing Census and the quarterly
updates are not analysed by the range of attributes as the national Employment Returns and the Labour Force Survey. As such, it offers a limited degree of interpretability. Household Income

Data published by the Department of Statistics on Household Income is as follows Household Income And Basic Amenities Survey
The Household Income Survey (HIS) has been conducted by the Department of Statistics, Malaysia since 1973. However, starting from 1987, The Basic Amenities Survey was conducted together with Household Income Survey and known as Household Income/Basic Amenities Survey (HIS/BA) and is carried out once every 5 years. The latest HIS/BA survey was carried out in 2009. The main objectives of the HIS/BA survey are to measure the economic well-being of the population; collect information on income distribution pattern of household classified by various socio-economic characteristics; identify the poor groups; collect information on basic amenities of household; and study the effects of the implementation of national development program. The name of the household head is collected in this survey, together with key identification data such i.e. NRIC number. Relevancy

Data for the 5-yearly census is highly relevant as it provides a view of household income from the point of view of the workers. Since respondents are identified by NRIC numbers in the census, the individualised data is highly resourceful for the Labour Market Information Indicators and Statistics. Accuracy

The data collected for the Household Income and Basic Amenities Survey is not verified against any documentary evidence such as pay-slips nor are they matched against other data sources such as Income Tax returns by the individual respondents. As such, the accuracy of data is dependent on the accuracy of data declared by the respondents. Timeliness

The Household Income and Basic Amenities Survey is published only once every 5- years. Therefore it may not reflect current market conditions in a timely manner. Acessibility
Data from the Household Income and Basic Amenities Survey may be obtained
from the Department of Statistics. Coherence
The household income and other data published for the Household Income and Basic Amenities Survey may be checked against othet published statistics such as National Employment Returns and Labour Force Survey for coherence. Intepretability

The data for Household Income and Basic Amenities Survey is analysed by a rich range of dimensions, and as such is highly interpretable. Business
The department of Statistics conducts the Business Tendency Survey to gauge business sentiments in the market. This provides indirect support for economic projections used to forecast demand for workers in the labour market. Business Tendency Survey

The Business Tendency Survey is conducted quarterly by the Department of Statistics, Malaysia since 2004. The survey gathers views from the senior management of 465 prominent establishments in four major sectors in Malaysia namely * industry,

* construction,
* wholesale & retail trade and
* services.
The main characteristic of this survey is to collect information regarding the direction of change of key economic variables. The Business Tendency Survey collects qualitative information from business managers on their assessment of the business performance for the past quarter and the expectations for the next three and six months. The information is useful for monitoring the current economic situation and its impact on the Labour Market environment. Identity of the respondents’ businesses and their actual and projected sentiments about the economic environment is collected for the immediate past and projected future quarters. The respondents are surveyed by the following sectorial categories * Agriculture

* Mining, electricity and water
* Manufacturing
* Construction
* Wholesale and retail trade
* Hotels
* Services (Transportation, Communication, Insurance, Real Estate and Information & Communication Technology) * Finance
Relevancy
Data from the Business tendency Survey provides support for estimates and projecting the growth of various industries for the purpose of projecting expected demand for labour. They are indirectly relevant to the Labour Market Information Indicators and Statistics but has to be processed to produce future estimates and projected growth or contraction in the labour market. Accuracy

Data from the Business Tendency Survey is based on business sentiments and is not “factual” in nature. Timeliness
The Business tendency Survey is conducted quarterly and as such has good timing to provide a timely assessment of the business sentiments prevailing on current market conditions. Acessibility
Data from the Business Tendency Survey may be obtained from the Department of Statistics. Coherence
Data from the Business Tendency Survey may only be checked against one another for commonalities in shared sentiments and overall confidence in the rates of growth. Intepretability
Data from the Business Tendency Survey is analysed by a rich set of attributes and as such are highly interpretable. Economic Census
The Department of Statistics conduct Economic Census every 5 years. The Census covers statistics from various industries * Agriculture
* Manufacturing
* Construction
* Mining and Quarrying
* Services
Relevancy
Data from the Economic Census provides a background for estimating and projecting the growth of various industries for the purpose of projecting expected demand for labour. They are indirectly relevant to the Labour Market Information Indicators and Statistics but has to be processed to
extrapolate the future estimates and projected growth. Accuracy

Data from the Economic Census is considered accurate as it involves a large number of respondents over many industries. Timeliness
Since the data from the Economic Census is collected once every 5 years, it is not considered timely to reflect changes in current market conditions. However, it is good enough for estimation and projection purposes. Acessibility

Data from the Economic Census may be obtained from the Department of Statistics. Coherence
Data from the Economic Census may be checked against other data sources such as industry publications from the Malaysian Palm Oil Board for coherence. Intepretability
Data from the Economic Census is analysed by a rich set of attributes and as such are highly interpretable. Economic Planning Unit, Prime Ministers Department
The Economic Planning Unit (EPU) is the government agency responsible for developing economic plans for the nation. In doing so the EPU performs the following activities * Collects statistics and indicators

* Analyses information and produces historical time series * Produces forecasts and projections
* Develops economic and transformation plans
The EPU’s input for the labour market information includes information on * Economic forecasts and plans
* Population and labour force studies
* Transformation plans
* Statistics on up-skilling programs (under NKEA)
The EPU publishes statistics in the following areas
* Population and manpower
* National account
* Agricultural products
* Industrial output indicators
* Public services
* External trade
* Balance of payment
* Price indices
* Social indices
* Economic indices
* Selected world indices
The following sets from the published statistics provide directly relevant data on Labour Market Information (number of workers) Population And Manpower
The Population and Manpower Statistics published by the EPU are * Population Size
1. By Age Group and Year (1891 – 2008)
2. 0 – 14
3. 15 – 64 (Working Age)
4. 65+
5. By Sex, Ethnic Group and Age (every 10 years where 2010 data is projected) 6. Age (Intervals of 5 years, from 0 to 70 and above)
7. Ethnic Groups (Malay, Other Bumiputras, Chines, Indians and Others) 8. By State
* Employment by Sector, Unemployment and Participation Rate by Year (1982 – 2007) * Data source from Department of Statistics
* Sectors are according to MIC 1972
* Agriculture, Livestock, Forestry and Fishing
* Mining and Quarrying
* Manufacturing
* Construction
* Electricity, Gas and Water
* Transport, Storage and Communications
* Wholesale & Retail Trades, Hotels & Restaurants * Finance, Insurance, Real Estate and Business Services
* Other services
* Immigrant Workers
9. By Country of Origin (1999-2008)
10. The countries of origin are: Indonesia, Bangladesh, Thailand, Philippines, Pakistan, Others 11. Sourced from Ministry of Home Affairs
12. By Sectors (1999-2008)
13. The sectors are: Maid, Manufacturing, Plantation, Construction, Services, Agriculture 14. Sourced from Ministry of Home Affairs
Relevancy
The Population and Manpower Statistics published by the Economic Planning Unit originates from the Department of Statistics, thus the assessment of these statistics refelects the assessment of the same statistics from the Department of Statistics. The Population and Manpower Statistics is highly relevant in providing data on the overall population, the working age population, the working population and unemployment. In terms of analysis, the data is analysed only by a few basic criteria such as gender, age group and ethnic composition. Attributes such as education level and areas of skillsets are not provided with the statistics and have to be extrapolated from other sources. Accuracy

Data published by the Economic Planning Unit on population and manpower is derived from data from the Department of Standards which is used as benchmark in various applications, thus it is considered accurate and usable. Timeliness

The data on population and manpower is published by the Economic and Planning Unit on an ad-hoc basis. Some of the statistics are only available up to the year 2008. Since the data originates from the Department of Statistics, which publishes more updated versions, the Department of Statistics is a better source of the same data in terms of timeliness. Acessibility

The data which originates from the Department of Statistics, may be sourced from the Department of Statistics directly. Coherence
Data for the statistics published by the Economic and Planning Unit may be checked against quarterly estimates produced by the Department of Statistics for coherence. Intepretability
The Population and Manpower Statistics is analysed only by basic attributes such as Age Group, Ethnicity and Gender. As such, it does not provide much room for interpretations. Industry Production Indices

The Industry Production Indices is useful for determining
* Trends in production growth/ contraction
* Correlation between employment and production by industry * Projecting production and employment

The Industry Production Indices published by EPU are
* Sourced from the Department of Statistics
* Provides annual indices from to 2008
* Provides indices for the Mining, Manufacturing and Electricity Industries Relevancy
The data for Industry Production Index is relevant in an indirect manner for the Labour Market Information Indicators and Statistics as it can be used to subjectively evaluate the growth and contraction prospects for the major industries, thereby projecting future demands for labour. The Industry Production Indices published by the Economic and Planning Unit is derived from data sourced from the Department of Standards. Thus, while the data is relevant in an indirect manner, the same data can be sourced out directly from the Department of Statistics. Accuracy

The Industry Production Index is considered accurate and reliable for estimating growth and contraction by broad-based industry categories as it used in various applications to benchmark economic growth. Timeliness

Many of the latest indices published by the Economic Planning Unit is for the year 2008. In view of many market changes since then, they cannot be considered timely. Acessibility
Source data for the indices may be obtained directly from the Department of Statistics. Coherence
Growth trends potrayed by the Industrial Indices may be compared with data from other sources such as statistics published by the Federation of Malaysian Manufacturers (FMM) or the Palm Oil Board to determine their coherence. Intepretability

The Indices are analyzed by very basic parameters, thus are not considered highly interpretable from multiple perspectives. They can be taken at face value. Statistics of Primary Agricultural Products

These statistics, sourced from the Department of Statistics, are published for the following agricultural products * Rubber
* Palm Oil
* Cocoa
* Forestry and Logging
And provide information (by year) on
* Number of Plantations
* Planted Hectarage (includes immature areas), by
* Plantations
* Smallholders
* Hectarage in Production
* Production
* Yield Per Hectare
* Average Price
* Number of Workers Employed
Relevancy
The Statistics of Primary Agricultural Products are produced from data originating from the Department of Statistics. They indicate past trends and the state of particular industries using industry specific parameters such as hectarage for agriculture. Some of the statistics publsih the number of employees involved in the particular industry. Most of these parameters are useful for determining future growth or contraction trends in particular industries. These industry growth or contraction parameters do not directly indicate the number of employees in demand as forecasted for the industry. That number has to be extrapolated and forecasted based on the industry growth or contraction parameters. As such, the data avaialble in these statistics are used directly in the Labour Market Information Indicators and Statistics. However, they are used indirectly in determining future trends of data in the Labour Market Information and Statistics, in particular the number of workers neded in a particular industry. The parameters reported in the statistics are quite basic. Where the number of workers employed in a particular industry is reported, the number is not elaborated with any further break down. Thus, the breakdown in number of workers may have to be extrapolated or incurred from the industry norm taken from other data
sources. The statistical data published by the Economic and Planning Unit is also useful for confirming statistics obtained from other sources. For example, the National Employer Returns and the Labour Force Survey also generates the number of workers employed by industry. The figures in the Statistics of Primary Agriculture Products may be used to verify that the estimates produced by the National Employment Returns and the Labour Force Survey are within reasonable range of accuracy. Accuracy

Data for the Economic and Planning Unit’s Statistics of Primary Agricultural Products is obtained from the Department of Statistics, a source which is used as a benchmark in many applications. Thus the data is deemed as accurate for its purpose. Timeliness

The Statistics of Primay Agricultural Products produced by the Economic and Planning Unit is dated several years back from the current year. As such, it is not considered timely for representing current market conditions. Since the data originates from the Department of Statistics, more recent data can be obtained from the Department of Statistics directly. Acessibility

Data for the Statistics of Primary Agricultural Products is derived from the Department of Statistics and may be obtained from there directly. Coherence
Data for the Statistics of Primary Agricultural Products may be checked against data generated by others sources such as the Malaysian Palm Oil Board for pal oil statistics in order to determine its coherence and reliability. Intepretability

Data for the Statistics of Primary Agriculture Products is elaborated by a limited number of parameters and as such offers a limited degree of interpretability beyond basic usage for trending. Conclusion

The list of indicators provided in section 8 and modes of their analysis provided in section 9 consolidates indicators from existing surveys and census reports in particular the Key Indicators for the Labour Market (KILM) and complements them with additional indicators to provide full coverage of the labour supply and demand situation in the Labour Market. Appendix 2
examines the availability of data from various data sources identified for this study to fulfill the needs of these indicators. The data in Appendix 2 is elaborated in the previous section. In this section we consolidate the view and identify choices of data sources to meet each indicator requirement. The analysis carried out in this section is supported by details in Appendix 1. To summarize our recommendations, since the levels of data that is availalable from various sources are some at the detailed individual levels (individual employers – identified by Company or Business Registration; individual employees identified by NRIC/ Household nos) or at aggregated levels (totals only, no individual identifiers); our recommendations are to set-up the data warehouse at two levels – An Aggregated Data Warehouse,and a Detailed Data Warehouse, as shown in the following diagram.

For the detailed Data Warehouse, where individual employers and employees are identified by key identifiers, data from various sources can either UPDATE the data (if it is in existence) or INSERT new data (if it is not existing) in the database, as shown below.

Data from various sources are valuable, since they may represent different cross-sections of the population (e.g.. SOCSO mostly covers only employees with salaries < RM3000), different data items (NER has more attributes than SOCSO) or update frequency (SOCSO is more frequently updated than NER). As such, the database design that we recommend take into account data for multiple sources inter-woven with one another, with the data source and time period identified, as follows.

Ultimately, data from various administrative sources, may be used to populate some of the data for National Employment Returns (NER) and Key Indicators for The Labour Market (KILM) as shown in the diagram below and as discussed in the following sections.

Employment Situation
Indicators and statistics on the employment situation cover situations where labour supply is matched with demand i.e. where labour is engaged in
employment. These include indicators that analyse employment by characteristics of the employers, such as industrial sector, size, location etc and indicators that analyse the characteristics of employees such as demographic profiles, geographical distribution, education attainment etc. These indicators provide insight into active employers and employees in the labour market Indicators On Employers

The indicators that provide insight into the characteristics of employers in the labour market.are * Number of employers
* Payroll costs incurred by employers
* Working hours set by employers
* Training budgets and costs incurred by employers

The indicators on employers are to be analyzed by the following dimensions * Geographical locations
* Industrial sectors
* Types of business ownership
* Equity ownership
* Size of paid-up capital
* Size of annual turnover
* Size of employed workforce
* Types of employment (direct recruits, outsourcing, part-time etc) * Compensation types practised (salaries, share of profits, bonuses, incentives, etc) * Compensation practices (rates schedule, employment benefits, promotions etc)

Data sources for Employers Data are as follows
* Ministry Of Human Resources
* SOCSO
* JobsMalaysia
* NER
* Department Of Statistics Malaysia
* Labour Force and Social Statistics
* Business Sentiment Survey
* Economic Census
* Economic and Planning Unit
* Population and Manpower Statistics
* Industry Production Indices
* Statistics of Primary Agricultural Products

None of the Employer data sources are able on its own to fulfill all the data requirements. In terms of comprehensiveness of attributes, the National Employment Returns published by the 2-year Manpower Department provides a rich number of attributes required to fulfill the needs of the Labour Market Information Indicators and Statistics, but not all of them. On the aspect of timeliness, however, the National Employment Returns is not published on a regular basis to reflect sudden changes in market conditions, which can happen within months and not years. With a 2-year publication schedule, there is a time lag in the timeliness of the data published in the National Economic Returns in representing current market conditions. SOCSO and JobsMalaysia provide data on employers on a “near” real time basis which is as and when employers register into their databases. Similar to the National Employment Returns, SOCSO and JobsMalaysia also provide employers’ data by each individual organization identified by their Business Registration Number or Company Registration Number. The Department of Manpower’s returns on disabled workers and employment agencies also provide some source of data on employers. However, these data sources do not provide broad coverage of all employers in the market. The returns on disabled workers is specifically good data source on disabled workers, a special interest group in the Labour Marke Information. There is the possibility of tapping into the SOCSO and JobsMalaysia databases to provide the Labour Market Information Indicators and Statistics during the interim period between updates of the National Employment Returns.This is possible because the SOCSO, JobsMalaysia and NER datasets all identify employers by their Business or Company Registration numbers, a common identifying key across all three, ensuring that there is no duplication of data leading to double counting of employers when the data is aggregated. The main shortcoming of the SOCSO and JobsMalaysia datasets however, as stated in the data quality assessment section, is that they do not cover the entire population of employers in the Labour Market. Most of the data from SOCSO covers only categories of employers with workers for
whom they make SOCSO contributions. Not all employers in the market employ workers with SOCSO contributions, based on the criteria given in the data quality assessment section. The data from JobsMalaysia, on the other hand, is based on voluntary registration and updates. Although an impressive number of employers had registered into its database, not all employers in the country has voluntarily registered with JobsMalaysia. As such. it is also not wholly representational of the employers population. The Labour Force and Social Statistics consists of the Labour Force Survey, Migration Survey and Wages and Salaries Survey produced by The Department of Statistics Malaysia. These are based on monthly surveys conducted by the department. Unlike the National Employment Returns, the unit of sampling used in these surveys are households and not employers. To a small degree, these surveys can provide information on employers, since some heads of household’s occupation are employers. However, these may cater only for small and medium scale industries where the businesses can be owned entirely by a household head, as opposed to companies and businesses owned by a pool of shareholders or by other corporations and organizations. Furthermore, employer’s data in the Labour Force Survey is not identified by a key identifier such as Company or Business Registration numbers, which can be used to determine whether an employer had been double counted in the returns of multiple households. Due to these reasons, the Labour Force and Social Statistics published by the Department of Statistics is not suitable as a basis for employer statistics. However, these surveys, which are based on household units, are very suitable for workers and employee statistics. As opposed to data on individual employers kept by the National Employment Returns, SOCSO and JobsMalaysia, the other data sources keep their data in aggregated and summarized forms (i.e. not by individual employers identified by Company Registration or Business Registration numbers) i.e. data from the Economic Census and Business Tendency Survey published by the Department of Statistics; and the Population and Manpower Statistics, Industry Production Indices and Statistics of Primary Agricultural Products published by the Economic and Planning Unit. The dimensional parameters by which the data from these aggregated and summarized data sources may be analyzed are also limited. These aggregated data sources may be used to complement the detailed data by providing comparisons to ascertain the accuracy and
coherence of the detailed data and extrapolations/ projections derived from them. The aggregated data also provides a broad-based basis for estimating and projecting trends into the future regarding employers in the labour market. In conclusion, our recommendation for fulfilling requirements on employers data involves taking the comprehensive bi-annual National Employment Returns as a basis for the Labour Market Information Indicators and Statistics and augmenting to cover it’s reporting period latency with administrative data from SOCSO (Form 1 – Employer RE and JobsMalaysia in between the publication of one National Employment Return and the next one. We also recommend using summarized and aggregated data from Economic Census and Business Tendency Survey published by the Department of Statistics; and the Population and Manpower Statistics, Industry Production Indices and Statistics of Primary Agricultural Products published by the Economic and Planning Unit as comparisons to determine the reasonableness and coherence of data and extrapolations/ projections produced from the detailed data from National Employment Returns, SOCSO and JobsMalaysia. These data may be combined into a summarized and detailed data warehouse where the data source and the frame period is identified. Detailed data gathered from administrative data sources such as SOCSO and JobsMalaysia may also be used to populate or update the National Employment Returns database on parameters available from these sources. Used in combination, the collection of data will be able to enhance the value of information available from any of the reports and statistics on a stand-alone basis. Combined with slice-and-dice and drill- down capabilities of a data warehouse, 360-degree analysis may be performed on the Labour Market Information. Combined with Business Intelligence Dashboards and Performance Scorecards, the data may be used for market/performance monitoring and triggering follow-up actions. Indicators On Employees

The indicators that provide insight into employees in the labour market are * Number of employees
* Amount of compensation received by employees, with the following details * Total monthly compensation
* Manufacturing wage indices
* Occupational wage indices
* Hourly compensation costs
* Starting salaries
* Years in employment
* Hours of work
* Number of part-time workers
* Employment in the informal sector
* Labour productivity

These indicators are analyzed into the following dimensions
* Geographical locations
* Industrial sectors
* Countries of origin
* Employee gender
* Ethnicity
* Education attainment
* Years of experience
* Age groups
* Marital Status
* Employment status
* Occupation
* Skill types possessed (Civil Engineering, Mechanical Engineering, etc) * Soft skill types possessed (Level of literacy, inter-personal communication, information technology, etc) * Membership in special focus groups (Aborigines, disabled, etc)

Data sources for Employees Data are as follows
* Ministry Of Human Resources
* SOCSO
* JobsMalaysia
* National Employement Returns (NER)
* JTK Forms for Disabled Workers
* Department Of Statistics Malaysia
* Labour Force and Social Statistics – Labour Force/ Migration/ Wages and Salaries Survey * Population And Demography – National Population and Housing Census * Household Income – Household Income and Basic
Amenities Survey * Business – Business Tendency Survey

* Economic Census
* Economic and Planning Unit
* Population and Manpower Statisics

None of the data sources on its own can provide all the require data. However, many of the data sources provide much of the required data. The data sources can be categorized by the degree of worker details handled. These are * Detailed data on individual worker (or represented head and members of households) – SOCSO, JobsMalaysia, Labour Force/ Migration/ Wages and Salaries Survey, National Population Census, Household Income and Basic Amenities Survey, JTK Disabled Workers * Detailed data on employers but aggregated data on workers employed – National Employment Returns, Business Tendency Survey * Aggregated data on employees – Economic Census by the Department of Statistics and Population and Manpower Statistics from Economic and Planning Unit One of the primary requirements of consolidating data on a detailed individual worker level into a single data set is the ability to identify the same worker across all data sources. This is to ensure that no worker is double counted in producing aggregations. This capability is only possible where the various data sources to be integrated share the same key identifier for each worker. In the case of Malaysian workers this would be the NRIC number. In the case of foreign worker and expatriates this would be the passport number in combination with country of origin. This requirement is not met across all the detailed data sources where data is kept by individual workers or heads of household. Those that utilizes the NRIC to identify workers are SOCSO, JobsMalaysia and Household Income and Amenities Survey (only available for heads of household with income less than or equal to RM12,000 per annum). The other surveys that capture data at individual worker/ household level uses a different household key to identify households. The National Population Census and Household Income and Basic Amenities Survey also captures some employment details for individual household members. For such data, the unit of granularity is household member while the unit of granularity of the survey is household heads. The household members are identified by household
identifier in combination with member number. Although the method of identification uses a different key from the head of household, from the standpoint of the labour market, the household members are also workers similar to the head of household. To cater for variations in methods of identifying individual workers, separate data sets are needed to identify them, based on differences in key identifiers used. Otherwise, there is no reliable means of ensuring that the same worker is double counted in the aggregations. Since data on employees is available at three different levels of summarization, three different strategies may be pursued to integrate and consolidate the data * separate sets of worker data will be kept at each available level of aggregation – this allows all data at all levels of details to be used in producing the Labour Market Information and Indicators, and detailed employee data may be linked to detailed individual employer data * aggregate all worker data to the highest level of consolidation before consolidating them – only employee data at the highest level of detail is available for analysis: details are lost in the aggregation and linkage to individual employer data is broken * aggregate individual worker data by their employers and use this in combination with aggregated worker data without employer details – detail of individual worker is lost in aggregation but aggregated employee data may be linked to detailed individual employer data With over 5 million contributor records, the employee data from SOCSO provides the most complete coverage of the worker population. Although this provides for breadth of coverage of the population, employee data from SOCSO does not cater for a number of the parameters required for employee data analysis such as Education Attainment and Skill Sets. A related aspect of the SOCSO data is that the parameters available for analysis do not conform with the standards required for analysing that Labour Market Information Indicators and Statistics, for example the occupation of employees do not conform to MASCO but is a free text field filed by the registering employer.The population of data from SOCSO is also limited to SOCSO contributors only according to the SOCSO contribution rules, which leaves the middle to upper end of the employment market out of the picture. Similarly workers from establishments that do not contribute to SOCSO such as self- employed persons. As such, data from SOCSO is good for a section of the population of workers albeit one with a
significant size, with a limited degree of interpretability due to its limited number of analytical parameters. JobsMalaysia does not primarily collect employee data. Rather, the portal collects data on job-seekers (who may be employed or unemployed). If the data is about unemployeds, then they turn into employees when jobs are matched to their applications. This being the case, the population of employee data in JobsMalaysis does not cover the entire population of employees as well. There is also no further guarantee that the job-seekers, once matched to jobs and employed, will continue to update the JobsMalaysia portal with their job progression, whether promotions or job changes. This may leave the data on the JobsPortal unreliable as a representation of current employee status as time passes. The detailed job-seekers data from JobsMalaysia, however, can be used as a basis for further survey and update of the employee data. These will provide a complementary data set to the employers’ data set that is used for National Employment Return, and the worker/ household data utilised in the Department of Statistic’s Labour Force Survey. Beginning with preliminary data from the JobsMalaysia database, random sampling of employees can be done to conduct further survey and data updates. The National Employment Returns (NER) provides a rich set of data on employees, albeit not at detailed, individual employee level. The shortcomings in the NER are as stated in the Evaluations section of this study and mainly has to do with skewness of data in the Labour Market Database which forms the pool for sampling for the NER. In terms of timeliness, the NER is published only once every two years, disconnecting it to current market conditions which can change in a matter of months. As mentioned in the conclusion on Employer Indicators, detailed administrative data from the SOCSO data set can be channeled into the NER data set whereby employer data (identified by Business or Company Registration numbers in both data sets) is either updated (where the data exists in NER) or created (where the data does not exist in NER), following which employee statistics about the respective employers can be updated to the NER database as well. A shortcoming of this activity, however, is again, that the data set from SOCSO does not have or does not conform to the rich analytical parameters required for NER. Also, the datasets from both SOCSO and JobsMalaysia do not include all employers in the country for reasons mentioned earlier. Facing these limitation, the
NER data set can still benefit from the SOCSO data by updating whatever available data can be obtained from SOCSO. The shortcoming in terms of the NER timeliness can be overcome if there is a source of recently and constantly updated data on employees to complement the bi-annual data collection of the NER. Thus the employee data from NER that is updated every 2 years can be inter-woven with employee data from other sources that is updated at more frequent intervals. Employee data sets that can be analysed by a rich set of dimensions may be obtained from The Department of Standards Labour Force and Social Statistics Surveys and Population and Demographic Studies, in particular the Labour Force Survey and the Household Income and Basic Amenities Survey. The Labour Force Survey, which is updated with monthly surveys is a good candidate for inter-weaving with the employee data in NER. The Household Income and Basic Amenities and the National Population and Household Census, which are conducted every 5 and 10 years respectively, do not contribute towards filling up the data gap between publications of the NER. However, the data from the Household Income and Basic Amenities survey and the National Population and Housing Census can be used to confirm the reasonableness of extrapolation of survey data to represent the population of workers in the NER. As and when the National Population and Housing Census and the Household Income and Basic Amenities are data are published, they can be added to the pool of Labour Information Indicators and Statistics data, provided that the data coming from data sources are kept segregated and identified by the data source and related time frame. The Department of Manpower’s Forms for disabled workers and employment agency returns do not provide total coverage of the workers population as they are based on voluntary reporting but they can provide some data on disabled employees and job matches which can be used as basis for sampling and extrapolation to represent the population of disabled and new employees. So as to realize the greatest degree of utilization and interpretability of data, we recommend that employee data be integrated suing the first strategy mentioned above. Using four separate storage areas and data sets, employee data at different levels of aggregations and details can be kept and analysed/ compared with one another * detailed individual employee data (identified by NRIC numbers) from SOCSO and JobsMalaysia is stored and linked together with detailed employer data. A subset of these data to
include detailed data on disabled workers from the JTK disabled workers forms. * detailed employee/ worker data (identified by household number an
d household member number) from the Labour Force/ Migration/ Wages and Salaries Surveys, the Household Income and Basic Amenities Survey and the National Population Census. Where NRIC numbers of the heads of households are available from the Household Income and Basic Amenities Survey, they should be linked to employee details gathered from SOCSO and JobsMalaysia using the NRIC as key for linking, if data from SOCSO and JobsMalaysia are also available for the particular workers/ employees.. * aggregated employee data (without individual employee data) is stored with detailed employer data from NER. This can also be complemented with forecasted number of employees from the Business Tendency Surveys. * aggregated worker statistics from the various Economic Census and industry statistics published by the Department of Statistics and the Economic Planning Unit. These four data sets provide some overlapping and some non-overlapping data and given that situation it is not possible to cross-substitute numbers from each other sources. For example, it is not possible to take a breakdown of total number of employees in the country categorized by occupation from NER and combine these with the total number of employees categorized by trained skilllsets from JobsMalaysia or combine them with total number of employees categorized by age groups from SOCSO, as each of these data sources represent a different pool of workers, some overlapping and some not. Further, broad-based statistics without any key identifier (the last group above) cannot be combined with one another but can only be left separated for comparison against one another. Therefore the approach taken is to provide separate data sets for each different pool and integrating different pools into one only where there exists a common key identifier enabling the integration into a common pool, at both the employees and employers levels. These separated data sets can then be analysed separately and processed manually for further extrapolation to represent the entire population of workforce in the country. Unemployment Situation

While indicators on the employment situation covers areas where demand and supply of labour are matched, indicators on the unemployment situation reports on situations of unemployment and under-employment due to mismatch
of demand and supply of labour. In a particular economy, both employment and non-employment may occur at the same time. Non-employment may be caused by a mismatch of circumstances affecting demand and supply, for example demand for a particular type of skill set may not be met by supply in a particular geographical area while the same skill set may suffer from over- supply in another geographical area. By providing 360- degree analytical capability, areas of mismatch between unfulfilled demands for labour and unemployed labour may be identified. Of all the data sources covered by the study, data on under-employment situation is available only from the Labour Force Survey as follows: For those aged 15 years and over, their activity status – either employed, unemployed or outside labour force – will be determined. Information collected from the employed include whether they had been working or not during the reference week, the number of hours worked, occupation, industry and status in employment, and if they have worked less than 30 hours per week, reasons and willingness to accept additional work. If they have not been working during the reference week but have a job to return to, the reasons for not working would be sought. The following questions will be sought to those who are unemployed: * action taken to look for work

* work experience
* duration of unemployment
Those who are classified outside labour force will be asked to state the reasons for not seeking work and working experience. The unemployment indicators consist of
Indicators On Under-Employment
These indicators consist of
* Number of persons who are under- employed (working less than 30 hours per week) It is analyzed by
* Geographical locations
* Persons’ country of origin
* Gender
* Ethnicity
* Educational attainment
* Age band
* Employment Status
* Marital Status
* Skill types
* Soft skill types
* Special groups
* Length of time being under-employed (by time period bands) * Reasons for under-employment
* Willingness to work more hours if provided? (yes/no)
* Other major activities carried out during under-employment The indicator provide insight into the degree of severity of the under- employment situation, where it is happening (by geographical as well as demographical boundaries) and the underlying causes of under-employment; with emphasis on particular special focus groups. Of all the data sources covered by the study, only the Labour Force Survey collects data on under-employment. The data collected on under-employment pertains only to the head of the household and not it’s individual members. Since the Labour Force Survey collects a rich set of attributes on the head of household, most of the analytical parameters required above is fulfilled. The Labour Force Survey is carried out monthly although it is published annually. This will provide a timely representation of the current labour market condition. JobsMalaysia may also be collecting data from under-employed workers looking for full employment. However, the data collected by JobsMalaysia is not sufficient identify under-employed persons (no hours of work) and as such cannot be used to collect data from them. The recommendation for data on under-employment situation is clear, to collect the data from the Labour Force Survey carried out monthly by the Department of Statistics. Since data in the Labour Force Survey does not identify respondents by their NRIC numbers, it is not possible to relate the data to other data sources that use the NRIC number to identify persons, such as SOCSO and JobsMalaysia. Additional insight may be gleaned from such relationships e.g.. employment history and work experiences of under-employed persons may be obtained from their employment history at SOCSO, but without a common identifier, this is not possible. Indicators On Un-Employment

These indicators consist of
* Number of persons who are unemployed (working less than 1 hour per week)

Further sub-indicators that cover specific areas of interest for unemployment are * Youth Unemployment
* Long Term Unemployment
* Time Related Unemployment

These indicators are analyzed by
* Geographical locations
* Persons’ country of origin
* Gender
* Ethnicity
* Educational attainment
* Age band
* Employment Status
* Marital Status
* Skill types
* Soft skill types
* Special groups
* Length of time being unemployed (by time period bands)
* Reasons for unemployment
* Whether the person had been looking actively for a job? (yes/no) * Type of activities carried out during unemployment

The indicators provide insight into the degree of severity of the un-employment situation, where it is happening (by geographical as well as demographical boundaries) and the underlying causes of un-employment; with emphasis on particular special focus groups. Indicators on the un-employment situation are captured in rich detail on the JobsMalaysia Portal and the data is updated frequently by walking registrants or through job fairs and similar events. Similarly, data collected through the Labour Force Survey permits comprehensive analysis of the unemployeds. However, data from JobsMalaysia cannot be combined with data from the the Labor Force Survey as JobsMalaysia uses the NRIC number as key identifier wherelse the Labour Force Survey uses household number. Therefore data from the two sources need
to be kept in separate storage areas or data sets and can be used to confirm each others’ patterns for reasonableness. The unemployed data at JobsMalaysia does not reflect the entire population of unemployeds as registration with JobsMalaysia is voluntary. Using data from JobsMalaysia as samples to be extrapolated into a representation of the population of unemployed is one way that the data can be used to provide Labour Market Information. The accuracy of data from JobsMalaysia, however, cannot be determined to be current. Job-seekers who register for jobs with JobsMalaysia but who find work elsewhere may not update their employment status at JobsMalaysia. There is a danger in relying on old data from JobsMalaysia due to the lack of assurance on data updates. Some further exploration may be necessary to determine the reliability of data by the age of the data in JobsMalaysia before selecting samples from it. Data from the Labour Force Survey is also derived from samples and extrapolated to represent the population. Since the Labour Force Survey is conducted monthly, the data reflects current labour market conditions in a timely manner. We recommend that data from both the Labour Force Survey and JobsMalaysia be tapped for data on the unemployment situation and to provide rich analysis of their parameters. Without a common key identifier, the data must be kept in two separate and uncombined data sets. They can be used to counter-check the reasonableness of data extrapolations carried out on samples of both as well as to support each other in terms of attributes that are lacking in one source but available in another. Demand For Labour

The Employment and Unemployment/ Under-Employment Indicators report on the size of employment and unemployment situation, but does not provide coverage on the size of demand for labour especially unfulfilled demand for labour. This is an area of particular interest to the nation as it aspires to become the status of a developed country, there are areas and niches of labour supply that faces acute shortages. These shortages in fact threatens the effort to industrialize the country as well as to transform it into a more effective knowledge economy.. Thus the following indicators report on the demand for labour (met and un-met), and consists of Economic Indicators – Actual And Forecast

Economic activities of the country play a major influence on demand for labour in the market. In particular, the level of exports, trade surplus and direct investments determine the health of the economy and creation of jobs. The following economic indicators are the basic ones required for historical time- series and projecting planned and forecasted impact of the level of economic activity on demand for labour in the market * Number of businesses

* Size and growth of Gross Domestic Product
* Size of Imports and Exports
* Investments and Foreign Direct Investments
* Inflation Rate
* Government Budget
* Employment Elasticity Studies

To be relevant for labour market analysis, these indicators are at least to be analyzed * By geographical locations (e.g. States)
* By country of origin (for number of businesses, size of imports/ exports, Investments, etc) * By industrial sectors
*
* There are two sources of economic indicators covered by the study: * Department of Statistics
* Business Tendency Survey
* Economic Census
* Economic and Planning Unit
* Industry Production Index
* Statistics of Primary Agricultural Products

However, the Economic and Planning Unit derives its statistics from the the Department of Statistics and lags behind the publication by the Department of Statistics. Thus, it is better to obtain the statistics directly from the Department of Statistics. The Department of Statistics publishes its economic census every 5-years. In terms of timeliness, this is insufficient to reflect changes in the economic environment which can occur rapidly and have a long term effect on trends in the labour market. There is no other
sources covered by study that provides the data at more regular intervals. To mitigate the timing delay in data availability, there are data sources outside the scope of this study that is updated more frequently. These data sources are commonly controlled by industry types. For example, the Malaysian Palm Oil Board publishes statistics on the palm oil industry, and the Federation of Malaysian Manufacturers publishes statistics on the manufacturing industry. Our recommendation is to construct a storage area or data set in the data warehouse with appropriate slots holding variables for the required indicators and their respective parameters for analysis over time. For a start, data can be accepted from the Economic Census conducted by the Department of Statistics, but subsequently, plans can be made to extract the same data from other available sources. The same data from multiple sources can be kept in the data warehouse for the sake of comparison, as long as they are identified by the source. Indicators On Manpower Shortages

While the economic indicators provide insight on the indirect impact of economic activity levels on the labour market, these indicators on manpower shortages provide coverage on actual shortages faced * Number of positions

* Length of time vacant

These are to be analyzed by
* Geographical location
* Industrial sector
* Educational attainment
* Skills required
* Soft-skills required

Indicators for Labour Requirements can be obtained from
* National Employment Returns – projected requirements for the next two years by occupation * Manpower Department – information on vacancies from employment agencies * JobsMalaysia – vacancies registered by employers

The National Employment Returns provide the most systematic collection of
information as it is a scheduled survey employing sampling and methods to extrapolate vacancies in the entire industry. However, skewness in the pool of sample may lean the data towards the needs of specific sectors and business sizes. The report on vacancies returned by employment agencies provide some information but may not be totally accurate or complete as prepared by the employment agencies. The JobsMalaysia database stores real vacancies reported by employers as and when the vacancies exist. Both can be combined to provide additional sampling data for extrapolating total need in the industry, and used in combination with the National Employment Returns to give a more comprehensive and balanced extrapolation of industry needs. The JobsMalaysia database is a rich data set on manpower demands and vacancies, where vacancies are analysed by a variety of analytical dimensions. To leverage maximally on the data that is available, we recommend that data from the three sources be combined using the employer Business or Company registration number as common identifying key. Records from all three sources may be combined into one storage area or dataset. Samples can then be selected from this pool and extrapolated to reflect the industry requirements for labour. Supply Of Labour

While the indicators for Labour Demand covers unfulfilled demand for labour, and unemployment covers existing surplus of labour supply, these indicators on the supply of labour covers situations that creates future and anticipated labour supply. They include indicators on persons in the labour-supply stream (education statistics) as well as supply of foreign labour that both complements and competes against domestic supply. The indicators that report on the supply of labour consists of Indicators On Population

These indicators report generally on the population of the country and consists of * Total population size
* Size of labour force
* Size outside labour force
* Employment to Population Ratio
* Employment Elasticities
* Population Education Attainment and Illiteracy

These indicators are to be analyzed by
* Geographical locations
* Persons’ country of origin
* Gender
* Ethnicity
* Educational attainment
* Age band
* Employment Status
* Skill types
* Soft skill types
* Special groups
* Reasons for being outside the labour force (for indicator of people outside the labour force)

Population Indicators are available from a number of sources, the most comprehensive being the 10-year National Population and Housing Census conducted by the Department of Standards. However, due to the interval of 10 years, the data may lose its timeliness over time. Other data is available on a sampling and survey basis only, but are more timely than the National Population Census and is accepted for use in various applications Our recommendation is to use data from the 10-year National Population and Housing Census as baseline and augment these with the more regularly published data on population in the monthly bulletin published by the Department of Statistics. Indicators On Education

The indicators on education report on future supply of labour by essential categories and consist of * Number of students
* Number of graduates
* Number of trainees
* Number of certificates issued
* Number of students working in the labour market

The indicators are to be analyzed into
* Geographical location of institutions
* Gender
* Ethnicity
* Skills/ Disciplines
* Soft-Skills Developed
* Educational Attainment
* Age Groups
* Employment status (for working students)

These indicators provide an insight into future entrants into the work force by types and levels of skills, as well as other categories.

None of the data sources covered by the study provide these information. Indicators On Foreign Labour
The indicators on foreign labour supply consists of
* Planned quota
* Number of persons (actual and forecasted)
* Number of cases of domestic labour outflow (locals working abroad)

These indicators are to be analyzed into
* Gender
* Country of Origin
* Age Group
* Education Attainment
* Skills Possessed
* Soft Skills Possessed
* Marital Status

The National Employment Return published by the Manpower Department provides the most comprehensive source of data on Foreign Labour with a rich set of analytical parameters for interpretation. Other data sources providing a similarly rich set of analytical parameters on workers data that is covered by the study are relevant only for local workers – SOCSO. JobsMalaysia, National Population and Housing Census and Household Income and Basic Amenities Survey. As such we recommend that data on foreign labour be obtained from the National Employment Returns. Benefiting From
Administrative Data

In this section, we answer the question of To What Extent Can Administrative Data Be Applied For Producing The National Employment Returns and generating Key Indicators For The Labour Market (KILM)? The application of administrative data as well as other data sources to produce each area of concern in Labour Market Information had already been examined component by component in the previous section. The concern in this section now is specific to the application of administrative data to produce the National Employment Returns and the Key Indicators of the Labour Market. Administrative Data Sources covered by the Study are

* SOCSO
* Manpower Department
1. JobsMalaysia Portal
Administrative Data Sources
In this section, we recap data that is available from administrative data sources covered by the study SOCSO
An employee employed under a contract of service or apprenticeship and earning a monthly wages of RM3,000 and below must compulsorily register and contribute to SOCSO regardless of the employment status whether it is permanent, temporary or casual in nature. An employee must be registered with the SOCSO irrespective of the age. SOCSO only covers Malaysian workers and permanent residents. As a result, foreign workers are protected under the Workmen’s Compensation Act 1952. Nevertheless, SOCSO does not cover the following categories of persons : * A person whose wages exceed RM3,000 a month and has never been covered before. * Government employees.

* Domestic servants employed to work in a private dwelling house which includes a cook, gardeners, house servants, watchman, washer woman and driver. * Employees who have attained the age of 55 only for purposes of invalidity but if they continue to work they should be covered under the Employment Injuries Scheme. * Self-employed persons.

* Foreign workers.
For the purpose of SOCSO contribution, wages mean all remuneration payable in money to an employee. The following payments are considered as wages : * salary
* overtime payment
* commissions and service charge
* payment for leave, sick, annual, rest day, public holidays, maternity and others * allowances, shift, incentive, housing, food, cost of living and others. * Payments made to an employee paid at an hourly rate, daily rate, weekly rate, task or piece rate are also considered as wages. However, the following payments are not considered as wages : * payments by an employer to any statutory fund for employees * mileage claims

* gratuity payments or payments for dismissal or retrenchment * annual bonus.
Employers are required to fill Employer Registration Form 1 and Employee Registration Form 2 for registration with SOCSO. Employer must fill both forms neatly providing complete details in a legible manner. A copy of the trading, business or company license has to be enclosed. The name of an employee has to be as per Identity Card. Both the new and old Identity Card numbers of the employee have to be entered. Thereafter, the duly filled forms and relevant documents should be sent to the SOCSO local Office which will then issue the employer with an employer’s Code Number within 1 month. This number will be used in all correspondence with SOCSO. Contributions should be made from the first month an employee is employed. Contributions can be made through appointed banks or through post offices in Sabah and Sarawak only. The detail records of contributions to SOCSO can be sent using * Computer tapes and diskettes

* Electronic data transfers
* Preprinted Form 8A
Administrative data relevant for analysis of Labour Market Information that can be obtained from SOCSO are SOCSO Employer Registration Form
Administrative data that can be obtained from Form 1 – SOCSO Employer Registration Form, is * Name of employer
* Company/ business registration number
* Address of employer
* Town (free text)
* Postcode (no State field)
* Telephone/ fax numbers
* e-mail address
* Year of registration
* Year of operation
* Type of ownership (sole proprietor/ partnership/ private limited company/ limited company/ others) * Type of industry (free text)
* Address of business location
* Date of first employee appointment
* Number of employees hired (cumulative to date of registration) * Salaries paid during month of registration
* Name, NRIC, address of owner/ managing director/ partner (combined free text) A sample of the form is included in Appendix 3.
SOCSO Employees Registration Form
Data that can be obtained from Form 2 – SOCSO Employee Registration Form, is * Name of employee
* NRIC number
* Date of birth
* Gender
* Ethnicity
* Date of employment
* Occupation (free text)
* Employer SOCSO Code
A sample of the form is included in Appendix 3.
SOCSO Monthly Contribution Form
Data that can be obtained from Form 8A – SOCSO Monthly Contribution Form is * Contribution month and year
* Payment type (cheque number/ cash)
* Employer code
* Employer name
* Employer address
* Employee name
* Employee NRIC number
* Employee date start/stop work
* Amount of contribution (no Salary field)
A sample of the form is included in Appendix 3.
Information on the SOCSO member/insured person (claims & benefits) SOCSO provides several types of claims and benefits for contributors. The claims data for these benefits can provide collaborative and additional information on employers and employees. These are the amongst claimable benefits provided by SOCSO

* Dependent Benefits
* Funeral Benefits
* Education Loan
* Permanent Disability Benefits
* Temporary Disability Benefits
* Accidental Death Benefits
Information that may be obtained from these claims include (depending on the nature of claim) information on the SOCSO member/insured person * Name of insured/employee
* NRIC number
* SOCSO number
* Date of accident/death
* Death certificate number
In the case of death, information on the claimant/ next-of-kin is also obtained * Name of claimant/ next of kin
* Relationship to member (widow/widower/eldest son/daughter/father/mother) * Name of dependents (aged 21 and below)
* NRIC of dependents
* Name of caretaker of dependents
* NRIC of caretaker
* Caretaker occupation
* Monthly income of caretaker
* Number of caretaker’s dependents
* Relationship to dependents
* Caretaker’s adddress
For permanent and temporary disabilities, information about the disabilities
and a doctor’s testimony is also obtained * Name of attending doctor
* Nature of complaint
* History of accident
* Physical examination details
* Pre-existing conditions
* Investigation results (lab test/ x-ray/etc)
* Diagnosis
* Treatment
* Period of medical leave
* Other remarks
For permanent and temporary disabilities, salary details for the last six months are obtained * Month and yesr
* Salary
* SOCSO contribution paid
Manpower Department
Administrative data available from the Manpower Department are JobsMalaysia Portal
JobMalaysia conducts activities to collect information on the Labour Market as follows * Registration of Employers
* Registration of Job Applicants (including students who are bout to enter the Job Market i.e. Final Year Students) * Registration of Vacancies
* Matching of Candidates to Jobs and Job Placements, on weekly, monthly and annual basis * Matching of jobs for applicants from Special Focus Groups 1. Disabled applicants
2. Pensioners
3. Youths
4. Unemployed graduates
5. Ex-convicts
6. Ex-drug addicts

In particular, JobsMalaysia is involved in preparing and furnishing information regarding the Labour Market in the following areas * Job Seekers
* Employers
* Job Opportunities/ Vacancies
* Job Placements
* Employment Trends
* Retrenchment Information
* Projections
Employer Information
The portal caters for the following types of employers
* Individuals
* Enterprises, Partnerships and Companies
* Associations, Embassies, International Associations
* Government Agencies
The following information is collected from employers during the registration process * Employer name
* Address
* Postcode
* Territory/ Division
* State
* e-mail address
* Web Address
* Phone and Fax Numbers
* Industry and Sub-Industry
* Whether interested or not to hire disabled
Employee Information
The following information collected from employees during the employee registration process * Name
* NRIC number
* Gender
* Marital status
* Race
* Nationality (for now restricted to Malaysians)
* Current job type (public sector/ private sector/ self-employed/ unemployed) * Address
* Postcode
* State
* District/ Division
* e-mail Address
* Telephone Number
* Mobile Phone Number
* Spoken Languages and Ability Levels (Fluent/ Good)
* Written Languages and Ability Levels
* Class of Driving License
* Other Licenses (e.g.. Scuba Diving)
* Applicant Category
1. School/ University Leaver
2. Seeking Career Enhancement
3. Laid Off Worker
4. Ex-Armed/ Police Force
5. Ex-Addict
6. Ex-Convict
7. Pensioner – Private Sector
8. Pensioner – Public Sector
9. Pensioner – Police
10. Disabled – Sight
11. Disabled – Speech
12. Disabled – Hearing
13. Midget
14. etc
* Education Level
15. Tertiary
16. Secondary
17. Primary
18. No Formal Education
* PMR/ SRP/ LCE Achievement
19. Year/ Grade
20. Subjects and Grade (maximum 10 only)
* SPM/ MCE/ SPM (V)/ SPVM Achievement
21. Year/ Grade
22. Subjects and Grade (maximum 10 only)
23. Bahasa Oral Test Result (Pass/ Fail)
* STPM/ STP/ HSC Achievement
24. Year/ Grade
25. Subjects and Grade (maximum 10 only)
26. Bahasa Oral Test Result (Pass/ Fail)
* PhD/ Masters/ Degree/ Diploma/ Certificate/ Final Year Student Achievement 27. Graduation Year
28. Qualification Level
29. CGPA/ PNGK
30. Instution
31. Is institution a foreign franchisee
32. Field of secialization
* Co-Curriculum Information
33. Sports field or Uniform Bodies/ Association/ Club
34. Level of achievement (International/ National/ State/ District/ Institution/ School) 35. Position (President/ Vice-President/ Secretary/ Treasurer/ Committee Member) 36. Work Experience (one only)

1. Company Name
2. Address
3. Position
4. Industry and Sub-Industry
5. Last Month Salary
6. Relevant Experiences (free text)
7. Unrelated Expereinces (free text)
8. Year Start
9. Year End
10. Reason For Leaving
Vacancy Information
The portal collects the following information on each vacancy * Name of position
* Description of position
* Length of vacancy
* Number of vacancies
* District and State of Vacancy
* Closing date for Applications
* Target Applicant Type (e.g. Pensioner)
* Working Hours (e.g. Normal)
* Offered Salary
* Gender
* Marital Status (e.g. Irrelevant)
* Contact Person, Phone Numbers and Cell Phone (2 persons) * Academic Achievement Level (Tertiary/ Secondary/ Primary/ No Formal Education) * Language Proficiency
* Age Group
* Vehicle Provided By Employer
* Type of Driving License Required
* Type of Professional License required
Others
The Manpower Department also collects data that is relevant on Labour Market through other minor processes such as those pertaining to employment agencies and the handicapped. These are:
* Registration of Vacancies from Employment Agencies
* Registration of Applicants for Employment
* Registration of Job Applicants from Disabled
* Registration of Employers for the Disabled
Data from these forms are described below:
Data on Employers
Data solicited from these sources contain the following information on employers * Name of employer
* Address
* Telephone/ fax numbers
* Nature of Business
For employers of disabled persons, additional information is collected * Registered address
* Type of industry
Data On Employees/ Job Applicants
Data solicited from these sources contain the following information on job applicants and employees * Name
* Address
* Date of Registration
* NRIC No
* Gender
* Qualification and Experience
For applicants that are successfully matched to employment placements * Name of employers
* Address of employers
* Starting salary
* Work position
For disabled persons, additional information is obtained
* Marital status
* Name of Association
* Contact person for association
* Type of disability
* Cause of disability
* Type of support equipment used
* Name of next-of-kin
* Address of next-of-kin
* Allergies (if any)
* Qualifications
* Experience
* Soft Skills
* Status of applicant (seeking employment/ working/ studying/ training/ others) * Salary range requested (per annum)
* Date employment is required
* Type of work seeked
* Location (area/ state) of work requested
* Special facilities requested (transportation/ accommodation/ railings/ toilets/ etc) Data On Job Positions/ Vacancies
Data from these sources contain the following information on job positions and vacancies * Name of Position
* Location of Work
* Job Requirements/ Pre-requisites
* Qualifications and Experience Requirements
* Number of Positions
* Date of Vacancy

For vacancies for the disabled, additional information is collected * Name
of positions
* Number of vacancies (by gender and type of disability)
* Minimum salary offered
* Minimum qualifications/ skills/ experience required
* Special amenities provided (transportation/ accomodation/ railings/ toilets/ etc) * Working environment (air-conditioned/ hot air/ dusty/ fans) Data Consumers
The Data Consumers are targets for Administrative Data. These are recapped from Section 7 specific for this consideration. National Employment Return
The National Employment Return is a special survey exercise undertaken bi-annually to collect data on the labour market. The first survey was conducted in 2007 and the latest in 2011. It’s coverage emphasises the characteristics of employers and employees, rather than employment and mismatches between labour demand and supply. Nevertheless, the parameters for data collected are detailed and exhaustive. The National Employment Returns are surveys conducted to obtain information on * Employers Profile and Composition

* Employees Profile and Composition
* Wage and Salary Levels
* Remuneration practices
Data Requirements
Data on Employers
The National Employment Return is based on employers as it’s unit of sampling. Data on employers collected by the NER are * Company name
* Business Company Registration Number
* SOCSO Number
* EPF Number
* PSMB Registration Number
* Operational Address/ Postcode/ Town/ District/ State
* Phone/ Fax/ e-mail
* Correspondence Address/ Postcode/ Town/ District/ State * Company’s Capital – Authorized and Paid-Up
* Year Started Operating
* Location of Industry (Free Trade Zone/ Industrial Area/ etc) * Paid-
Up Capital
* Year Commenced Business
* Equity Ownership
* Bumiputra
* Non-Bumiputra
* Partnership between Bumi and Non-Bumi status companies * Local and Foreign Between Local and Foreign
* Foreign Only
* Type of Ownership
* Sole Proprietorship
* Partnership
* Private Limited Company
* Public Limited Company
* Co-Operative
* Organisation
* Society
* Non-Profit Private Organization
* Method of Employing Workers
* Using Labour Contractor/ Outsourcing Company and Number Recruited * Part-Time Workers/ Home Working and Number Recruited
* Direct Intake/ Recruitment and Number Recruited
* Whether the Company has internal mechanism to prevent sexual harassment (Yes/ No) * Whether the company provide Employer/ Employee relation mechanism * Number of Special Class Employees

* By Category (Aborigine/ Disabled/ Ex-Drug Addicts/
* By Level (Executive/ Non-Executive)
* By Gender (Male/ Female)
* Employment Practices
* Is bonus determined according to employee performance? * Is bonus based on Company Profit?
* Is salary increment based on employee performance?
* Does company pay on piece rate basis?
* Does the company has an employer’s trade union? (provide name) * Does the company has an employee trade union? (provide name) *
Whether the company pays the following allowances

* Shift allowance
* Attendance allowance
* Incentive allowance
* Food allowance
* Transport allowance
* Housing allowance
* Laundry allowance
* Cost of living allowance
* Service allowance
* Outstation allowance
* Entertainment allowance
* Telephone allowance
* To enumerate 3 other allowances if practised (free text) * Whether the company provides the following facilities to employees * Housing
* Hostel
* Water supply
* Electricity
* Medical treatment
* Dental treatment
* Prayer room
* Nursery
* Sports and recreation facilities
* Courses and training
* Group insurance
* Uniform subsidies
* To enumerate 3 other benefits if practised (free text) * Industry (according to MSIC section and part)
* Products and services produced by Company (free text)
* Is product for local market? (yes/ no)
* Is product for export market? (yes/ no)
* Percentage of products exported
* Minimum and maximum bonuses paid for
* Executive staffs
* Non-executive staffs
* Medical benefits cost for the year
If the company provides training for employees, to provide (all free text) * Name of training course
* Cost per person
* Number of participants
* Venue of course
* State countries of export (free text)
Worker Particulars
The following aggregated data (in total and not by individual employee) is collected for local workers * Number of employees (by gender)
* Number of disabled employees (by gender)
* Total basic wages (by gender)
* Total overtime hours (by weekday, restday and public holiday) * Total overtime wages (by wekday, restday and public holiday) * Total cash allowances
* Average salary increment
The following aggregated data is collected for foreign workers (by country of origin) * Number of employees (by gender)
* Total basic wages (by gender)
* Total overtime hours (by weekday, restday and public holiday) * Total overtime wages (by wekday, restday and public holiday) * Total cash allowances
* Average salary increment
Whereby the data is categorized under the following groups of workers * Managers
* Professionals
* Technicians and Associates
* Clerical
* Services and Sales
* Skilled Agricultural, Forestry and Fishery Workers
* Craft and Related Trades Workers
* Plant and Machine Operators and Assemblers
* Elementary Occupation Workers
The number of workers is analyzed by the following categories * Age Group
* Below 14
* 14 – below 16
* 16 – below 18
* 18 – below 25
* 25 – below 40
* 40 – below 55
* 55 – below 58
* 58 – below 60
* 60 – below 65
* 65 and above
* Local workers by racial breakdown
* Malay
* Chinese
* Indians
* Other Bumiputeras (e.g. Orang Asli)
* Sabah Citizen (all Sabah Citizens working in Peninsular Malaysia, bumiputra and non-bumiputra) * Sarawak Citizen (all Sarawak citizens working in Peninsular Malaysia, bumiputra and non-bumiputra) * Others

* Non-Citizen Workers
* Expatriates (Non-citizen workers working in Malaysia in top management level/ management and professional or technical skills posts which require experience and related technical skills, approved by the relevant Expatriate Committee (EC) * Foreign Workers (Non-citizen workers who do not have any professional qualification, experience and technical skills Projected new jobs and manpower requirements

* Name of occupation
* Status of position (permanent, temporary or contractual * Academic qualifications (if job requirements SPM or equivalent and above) * Offered salary (workers without experience)
* Offered salary (workers with experience)
* Number of workers needed for next 2 years
Note that that survey collects only the aggregated data (e.g. number of
workers) in each category cited above. It does not collect detailed employee data such as name and NRIC number. Wage Particulars

Particulars of wages are collected from employers according to the MASCO categories of occupation (Major Groups and Sub- Major Groups). Employers return the number of employees falling in each Salary Range.The data is analysed into * Occupation (MASCO Major Group and Sub-Major Group)

* Local Worker, Expatriate or Foreign Worker
* Race (Malay, Chinese, Indian, Other Bumiputras, Sabah Citizen, Sarawak Citizen, Others) * Salary Band
1. Below RM350
2. RM 350-399
3. RM 400-549
4. RM 550-699
5. RM 700-999
6. RM 1,000-1,499
7. RM 1,500-1,999
8. RM 2,000-2,499
9. RM 2,500-2,999
10. RM 3,000-3,999
11. RM 4,000-4,999
12. RM 5,000-6,499
13. RM 6,500-7,999
14. RM 8,000-10,999
15. RM 11,000-13,99
16. RM 14,000 and above
The starting wage for each occupation can also be obtained by * Occupation (MASCO Major Group and Sub-Major Group)
* Local Worker, Expatriate or Foreign Worker
* Race (Malay, Chinese, Indian, Other Bumiputras, Sabah Citizen, Sarawak Citizen, Others) Data Avaialability
Evaluation
Key Indicators For Labour Market (KILM)
The data requirement for Key Indicators For The Labour Market are as
described in Section 8. Evaluation
National Employment Returns
Data On Employers
The National Employment Returns presently uses the Labour Market Database (LMD) as source for sampling in conducting the bi-annual survey. Can administrative data from SOCSO and the Manpower Department add value to the National Employment Return by providing data from their databases? Both SOCSO and JobsMalaysia Portal uses the employers’ Business Registration or Company Registration Number as key identifier. This is in synchronicity with the National Employment Returns, which also uses the same key identifier for employers. Employers’ data can thus be obtained from SOCSO and JobsMalaysia Portal and channeled to the National Employment Returns either as new records for employers without any previous record in the National Employment Returns or as updates to existing records for employers with existing records. Data from SOCSO that may be used for National Employment Returns are * Name of employer

* Company/ business registration number
* Address of employer
* Town (free text)
* Postcode (no State field)
* State (derived from postcode)
* Telephone/ fax numbers
* e-mail address
* Year of registration
* Type of ownership (sole proprietor/ partnership/ private limited company/ limited company/ others – National Employment Returns requires breakdown of the Others category) * Type of industry (requires re-coding into the MSIC categories used by National Employment Returns) Data from JobsMalaysia that may be used for National Employment Returns are * Employer name

* Address
* Postcode
* Territory/ Division
* State
* e-mail address
* Phone and Fax Numbers
* Industry and Sub-Industry
As such, the data on employers required by National Employment Returns can be satisfied by SOCSO and JobsMalaysia are as follows * Company name (available)
* Business Company Registration Number (available)
* SOCSO Number (available)
* EPF Number (Not available)
* PSMB Registration Number (Not available)
* Operational Address/ Postcode/ Town/ District/ State (available) * Phone/ Fax/ e-mail (available)
* Correspondence Address/ Postcode/ Town/ District/ State (available) * Company’s Capital – Authorized and Paid-Up (not available) * Year Started Operating (Available from SOCSO only)
* Location of Industry (Free Trade Zone/ Industrial Area/ etc) (Not available) * Paid- Up Capital (Not available)
* Year Commenced Business (Available)
* Equity Ownership (Not available)
1. Bumiputra
2. Non-Bumiputra
3. Partnership between Bumi and Non-Bumi status companies 4. Local and Foreign Between Local and Foreign
5. Foreign Only
* Type of Ownership (Available subject to breakdown of Others as noted above) 6. Sole Proprietorship
7. Partnership
8. Private Limited Company
9. Public Limited Company
10. Co-Operative
11. Organisation
12. Society
13. Non-Profit Private Organization
* Industry (according to MSIC section and part) (Only from JobsMalaysia,
requires re-codification from SOCSO) The following data is not available from JobsMalaysia and SOCSO. * Method of Employing Workers

* Using Labour Contractor/ Outsourcing Company and Number Recruited * Part-Time Workers/ Home Working and Number Recruited * Direct Intake/ Recruitment and Number Recruited
* Whether the Company has internal mechanism to prevent sexual harassment (Yes/ No) * Whether the company provide Employer/ Employee relation mechanism * Number of Special Class Employees

* By Category (Aborigine/ Disabled/ Ex-Drug Addicts/
* By Level (Executive/ Non-Executive)
* By Gender (Male/ Female)
* Employment Practices
* Is bonus determined according to employee performance? * Is bonus based on Company Profit?
* Is salary increment based on employee performance?
* Does company pay on piece rate basis?
* Does the company has an employer’s trade union? (provide name) * Does the company has an employee trade union? (provide name) * Whether the company pays the following allowances

* Shift allowance
* Attendance allowance
* Incentive allowance
* Food allowance
* Transport allowance
* Housing allowance
* Laundry allowance
* Cost of living allowance
* Service allowance
* Outstation allowance
* Entertainment allowance
* Telephone allowance
* To enumerate 3 other allowances if practised (free text) *
Whether the company provides the following facilities to employees * Housing
* Hostel
* Water supply
* Electricity
* Medical treatment
* Dental treatment
* Prayer room
* Nursery
* Sports and recreation facilities
* Courses and training
* Group insurance
* Uniform subsidies
* To enumerate 3 other benefits if practised (free text) * Products and services produced by Company (free text)
* Is product for local market? (yes/ no)
* Is product for export market? (yes/ no)
* Percentage of products exported
* Minimum and maximum bonuses paid for
* Executive staffs
* Non-executive staffs
* Medical benefits cost for the year
* If the company provides training for employees, to provide (all free text) * Name of training course
* Cost per person
* Number of participants
* Venue of course
* State countries of export (free text)
Data On Employees And Wages
JobsMalaysia does not collect data on employees per se. Rather, JobsMalaysia collects data on job-seekers. Where current employees register as jobseekers with JobsMalaysia, they do not provide the Business Registration or Company Registration numbers to enable their registration with the portal to be linked to their employer data while the National Employment Returns uses the employer’s Business Registration Code or Company Registration number to
identify employers.. As such, JobsMalaysia does not provide any useful data on employees in a manner that can be integratedinto the existing National Employer Returns data structure. SOCSO collects the following data on employees through the Employee Registration Form (Form 2): * Name of employee

* NRIC number
* Date of birth
* Gender
* Ethnicity
* Date of employment
* Occupation (free text)
* Employer SOCSO Code
Additionally, data on employees that can be derived from Monthly SOCSO Contribution Form (Form 8A) are * Contribution month and year
* Payment type (cheque number/ cash)
* Employer code
* Employer name
* Employer address
* Employee name
* Employee NRIC number
* Employee date start/stop work
* Amount of contribution (no Salary field)
Note that remunerations received by employee is subject to those which attracts SOCSO contribution and may only be estimated by working backwards from the contribution amount using the SOCSO Contribution Schedule. Fulfilment of data on employees required by the National Employment Returns are * Number of employees (SOCSO only reports on employees who contribute to SOCSO) * Number of disabled employees (by gender) – Available only for employees who become disabled and seek benefits from SOCSO during employment, does not include e.g. employees who are disabled at the point of appointment * Total emoluments (remuneration components that attract SOCSO) may be estimated by working backwards using SOCSO contribution schedule, but breakdowns into remuneration component is not available * Total basic wages (by gender) – Not available subject to above * Total
overtime hours (by weekday, restday and public holiday) – Not available subject to above * Total overtime wages (by wekday, restday and public holiday) – Not available subject to above * Total cash allowances – Not available subject to above

* Average salary increment – Average increment of remuneration attracting SOCSO may be worked backwards from contribution amount as stated above Data is required for foreign workers (by country of origin) is not available as SOCSO is only applicable for Malaysians * Number of employees (by gender)

* Total basic wages (by gender)
* Total overtime hours (by weekday, restday and public holiday) * Total overtime wages (by wekday, restday and public holiday) * Total cash allowances
* Average salary increment
Categorization of workers under the following groups need to be re-coded from SOCSO’s free text Occupation field * Managers
* Professionals
* Technicians and Associates
* Clerical
* Services and Sales
* Skilled Agricultural, Forestry and Fishery Workers
* Craft and Related Trades Workers
* Plant and Machine Operators and Assemblers
* Elementary Occupation Workers
The number of workers is analyzed by the following categories * Age Group (may be calculated from Date of Birth)
* Below 14
* 14 – below 16
* 16 – below 18
* 18 – below 25
* 25 – below 40
* 40 – below 55
* 55 – below 58
* 58 – below 60
* 60 – below 65
* 65 and above
* Local workers by racial breakdown (Available from SOCSO) * Malay
* Chinese
* Indians
* Other Bumiputeras (e.g. Orang Asli)
* Sabah Citizen (all Sabah Citizens working in Peninsular Malaysia, bumiputra and non-bumiputra) * Sarawak Citizen (all Sarawak citizens working in Peninsular Malaysia, bumiputra and non-bumiputra) * Others

* Non-Citizen Workers (Not available from SOCSO)
* Expatriates (Non-citizen workers working in Malaysia in top management level/ management and professional or technical skills posts which require experience and related technical skills, approved by the relevant Expatriate Committee (EC) * Foreign Workers (Non-citizen workers who do not have any professional qualification, experience and technical skills – Not available Key Indicators For Labour Market (KILM)

KILM is a multi-functional research tool of the ILO consisting of county-level data on 20 key indicators of the labour market from 1980 to the latest available year. The first KILM was released about 10 years ago. It has since become a flagship product of the International Labour Office (ILO). The first Key Indicators of the Labour Market (KILM) was released in 1999. It has since become a flagship product of the International Labour Office (ILO) and is used on a daily basis by researchers and policy-makers throughout the world. At the national level, statistical information is generally gathered and analysed by statistical services and ministries. At the global level, the ILO plays a vital role in assembling and disseminating labour market information and analysis to the world community. The KILM is a collection of 20 “key” indicators of the labour market, touching on employment and other variables relating to employment (status, sector, hours, etc.), the lack of work and the characteristics of jobseekers, education, wages and compensation costs, labour productivity and working poverty. Taken together, the KILM indicators give a strong foundation from which to begin addressing key questions related to productive employment and
decent work. The KILM is:

* a comprehensive database of country level data on 20 key indicators of the labour market from 1980 to the latest available year. In this context, the KILM can serve as a tool for policy makers and researchers in monitoring and assessing many of the pertinent issues related to the functioning of labour markets. * a source of the latest ILO world and regional estimates of employment and unemployment indicators. * a training tool on development and use of labour market indicators. Each indicator is accompanied by descriptions of the standard international definition of the concept and measurement procedures, guidelines on how the indicator can be used in analyses of labour market issues, and words of cautions on comparability limitations. Readers are guided on the value of using multiple indicators to develop a broader view of labour market developments. * highlights of current labour market trends. The trends identified in an analysis of each indicator accompany each indicator manuscript, with graphics to display results. * analysis of key issues in the labour market.

The Key Indicators for Labour Market Malaysia (KILMM) adopts the indicators from Internation Labour Organization (ILO) but excludes the following indicators * Employment In The Formal Sector
* Part Time Workers
* Manufacturing Wages Indices
* Occupational Wages Indices
* Hourly Compensation Costs
* Poverty, Working Poverty and Income Distribution
* Labour Productivity
* Employment Elasticities
On the other hand, KILMM adds another indicator to the set
* KILM 13: Inactive Rate
These indicators are summarised in their respective sections below, by referring to International Labour Organization(ILO), Department of Statistics Malaysia(DOSM). When the measures and dimensions identified in for the Summary Indicators and Statistics section above have been fulfilled,
the requirements of the Key Indicators for the Labour Market (KILM) will also be fulfilled as KILM is a subset and may be calculated from the set of measures and dimensions. Labour Force Participation Rate

The number of employees registered with SOCSO does not cover all the employees in the market SOCSO contribution is only applicable to salaried workers earning RM3,500 and below. However, the employee data that is available may be used to categorize employees by gender, ethnicity, age groups, etc. JobsMalaysia covers more of jobseekers than employees. Although some of the jobseekers on JobsMalaysia may be current employees in the market, registration with JobsMalaysia is voluntary and as such does not represent the number of all employed persons in the market. Employment-To-Population Ratio

The number of employees registered with SOCSO does not cover all the employees in the market SOCSO contribution is only applicable to salaried workers earning RM3,500 and below. However, the data from SOCSO may be used for extrapolating breakdown by categories such as gender, age group and ethnicity subject to the skewness mentioned. JobsMalaysia covers more of jobseekers than employees. Although some of the jobseekers on JobsMalaysia may be current employees in the market, registration with JobsMalaysia is voluntary and as such does not represent the number of all employed persons in the market. Status In Employment

The status of employment criteria is not requested from in SOCSO although most of SOCSO contributors are employed full-time. JobsMalaysia requests the following information from its job-seekers – Current job type (public sector/ private sector/ self-employed/ unemployed), but since its database does not represent the entire population of workers/ job-seekers in the labour market, it can only be used as a basis for sampling and extrapolation. Employment By Sector

Sectoral information is registered by employers with SOCSO as a free text field and can be used with re- codification into the MASCO categories. Sectoral information of existing jobs is not collected from job-seekers in
JobsMalaysia. Hours Of Work

Hours of work information is not collected from SOCSO and JobsMalaysia. Unemployment
SOCSO does not cover unemployed persons. The data from JobsMalaysia include categorization of job-seekers who are unemployed, however since registration with JobsMalaysia is on a voluntary basis (as is also the updating of its database by persons who were unemployed but subsequently found employment) – the data from JobsMalaysia is useful as a pool for extraction of samples that need further verification. Youth Unemployment

The same limitations for Unemployment applies to Youth Unemployment Long Term Unemployment
The same limitations for Unemployment applies to Long Term Unemployment Time Related Underemployment
The same limitations for Unemployment applies to Time Related Unemployment Inactive Rate
Individuals are considered to be outside the labour force, or inactive, if they are neither employed nor unemployed, that is, not actively seeking work. These persons would not be registered as active contributors to SOCSO nor would they register themselves as job-seekers with JobsMalaysia. Inactive contributors to SOCSO may be canvassed and contacted for additional information to determine whether they fall under this class. Educational Attainment and Literacy

SOCSO does not collect this information.
Information from JobsMalaysia on skills and soft-skills may be useful for this purpose. The data from JobsMalaysia may be used for extraction of samples for further process of analysis and extrapolation to represent the population. Employment In The Informal Sector

Typically, workers in the informal sector are not registered with SOCSO. Job-Seekers in JobsMalaysia are not asked questions which would determine whether they work in the informal sector. Part-Time Workers

The indicator on part-time workers focuses on individuals whose working hours total less than “full time”, as a proportion of total employment. The ILO defined “part-time worker” as “an employed person whose normal hours of work are less than those of comparable full-time workers”. Data collected by SOCSO and JobsMalaysia are do not include working hours and are insufficient to differentiate full time from part time workers. Poverty, Working Poverty And Income Distribution

Remuneration estimates from SOCSO may be used to identify workers who live below the poverty level. Although SOCSO contributors do not come from all types of workers in the labour market, the data that is available may be used as samples to represent certain sectors of the population. Labour Productivity

Productivity data is not available from SOCSO or JobsMalaysia Conclusion
These are the conclusions formed on the use of administrative data sources covered by the study to fulfill data requirements of the National Employment Returns and Key Indicators of The Labour Market. National Employment Returns

On employers data, 10 out of over 35 data items required by the National Employment Returns, may be obtained from SOCSO and JobsMalaysia with only 2 or 3 requiring re-codification effort. This represents 28 percent of the data items required. Most importantly, key and essential data items for identifying employers (name, address, business/ company registration numbers) may be obtained from the administrative data sources. These allow the National Employment Return to tap on the 340,000 over active employers to supplement those not yet on the Labour Market Database for sampling and augmented data collection purposes. On employees data, 5 out of 11 required data items for local employees is available (45 percent). The most fundamental data – remunerations, is neither declared on the Employee Registration Form (Form 2) nor the Monthly Contribution Form (Form 8A). Only the amount of contribution is stated in the Monthly Contribution Form, necessitating to work backwards using the SOCSO Contribution Schedule to estimate the amount of remunerations. The amount of remuneration thus does not have the breakdowns required for Netional Employment Income, and it goes
by the definition of remunerations that attract SOCSO contribution. Employees whose data are reported by SOCSO in the majority is limited to those required by law to contribute, in general those earning RM3,000 or below. Thus the data from SOCSO may be skewed to certain rungs of and types employees. Key Indicators For Labour Maket

Data from the large administrative data sources covered by the study, SOCSO and JobsMalaysia may be used for 6 of the KILM Indicators (33 percent) subject to skewness in the data composition (workers who contribute SOCSO mostly earn RM3,000 and below). Data Integration And Processing

Data Integration between the Related Agencies

Figure 9.1: Conceptual Diagram for LMDW Data Integration

Data integration is important in providing the gathered information from the various department or agency. The data sources from the related departments or agencies may vary. The possible format of the data sources are:

* Digital data (ASCII or text format)
1. If the data source can be retrieve from the existing database (related agencies server), we will generate ASCII or text file from the database. The type of database used by the agencies may vary. To ensure all the data can be retrieve and extract to the new database, we have to generate ASCII or text file from the existing database. The ASCII or text file from the related agencies will be extracted into our Labour Market Data Warehousing (LMDW) database. * Hardcopy

* If the data source is from the hardcopy, we have to do the data entry process. The data entry application must be used in order to key-in the information needed into the LMDW database. The process will take some time to complete depending on how much information from the hardcopy must be keyed-in. The hardcopy mentioned may come from several sources such as Forms, Reports or Questionnaires produced by the agency. In this case the agency is SOCSO.

Data from the related agencies will be combined into one database which we call it LMDW database. When all the data from the data sources combined into LMDW database, the data is ready to be retrieved and used. The data can be digest accordingly depends on the requirement or report. When we have all the data from the various agency gathered into LMDW database, we can digest the data to generate a report or forms needed by MOHR especially ISMK. In order to digest the data, we need to develop an application base on the ISMK’s requirements. In this case, the application will have the ability to produce reports and forms needed for NER, KILM and others.

Below is the illustration on how the data source from SOCSO, are gathered and integrated into the LMDW Datawarehouse.

In this example, there are two types of data source which are: * Extracted from the SOCSO’s database.
* Extracted from Forms, reports and questionnaires.

Extraction of the SOCSO’s Database
In this exercise, we will configure the connection from SOCSO’s database to the LMDW database. The information needed for the NER will be identified and some information may be extracted from the SOCSO’s database. The identified information then will be searched and mapped into table. The information, indicators or statistics that will be extracted from the database are based on four (4) key areas which are: * Employment Situation

* Unemployment Situation
* Demand for Labour
* Supply of Labour

The identified administrative data from SOCSO’s database will be extracted and converted into ASCII format. The data in ASCII format then will be push to the LMDW Datawarehouse Server. This task will be configured and scheduled automatically among the databases. So the information will be updated instantly in LMDW’s database when there are changes in the SOCSO’s database.
The completeness of the data gathered in the LMDW database depends on the data source of the administrative data extracted from. The more agency involve, the more information gathered. The higher percentage of the information gathered, automatically will help MOHR in producing complete report such as NER or KILM.

Extraction from Forms, Reports and Questionnaires
In this exercise, we have to develop a data-entry application. A dedicated team will be assigned to extract the related administrative data from data source (forms, reports and questionnaires) and key-in into the temporary database before we verify and push it into the LMDW database. This activity will continue until all the analog data are collected and will be digitally accessed after the verification process complete. The verification process will be done by MOHR officer so that all data inserted into the LMDW database are cleaned and suite the MOHR’s requirement. The information, indicators or statistics that will be extracted from the hardcopy are also based on four (4) key areas which are: * Employment Situation

* Unemployment Situation
* Demand for Labour
* Supply of Labour

LMDW advantages to ISMK
* Faster to retrieve the information needed. Eighty percent (80%) of the information will be automatically filled into the forms or reports. * Through the LMDW database and the application, reports and forms can be generated accordingly. * In this case, the agencies involved are DOS, EPU, SOCSO and JTK. In this exercise, may be not all data needed for the reports available in the LMDW database. In order to furnish all the data, data source from other agency needed. May be in next exercise or project, ISMK will determine which agency involved. Extraction Of SOCSO Database

In this exercise, we will configure the connection from SOCSO’s database to the LMDW database. The information needed for the NER will be identified and
some information may be extracted from the SOCSO’s database. The identified information then will be searched and mapped into table. The information, indicators or statistics that will be extracted from the database are based on four (4) key areas which are: * Employment Situation

* Unemployment Situation
* Demand for Labour
* Supply of Labour

The identified administrative data from SOCSO’s database will be extracted and converted into ASCII format. The data in ASCII format then will be push to the LMDW Datawarehouse Server. This task will be configured and scheduled automatically among the databases. So the information will be updated instantly in LMDW’s database when there are changes in the SOCSO’s database. The completeness of the data gathered in the LMDW database depends on the data source of the administrative data extracted from. The more agency involve, the more information gathered. The higher percentage of the information gathered, automatically will help MOHR in producing complete report such as NER or KILM. Extraction From Forms, Reports and Questionnaires

In this exercise, we have to develop a data-entry application. A dedicated team will be assigned to extract the related administrative data from data source (forms, reports and questionnaires) and key-in into the temporary database before we verify and push it into the LMDW database. This activity will continue until all the analog data are collected and will be digitally accessed after the verification process complete. The verification process will be done by MOHR officer so that all data inserted into the LMDW database are cleaned and suite the MOHR’s requirement. The information, indicators or statistics that will be extracted from the hardcopy are also based on four (4) key areas which are: 1. Employment Situation

* Unemployment Situation
* Demand for Labour
* Supply of Labour
LMDW Advantages To ISMK
1. Faster to retrieve the information needed.
2. Through the LMDW database and the application, reports and forms can be generated accordingly. 3. In this case, the agencies involved are DOS, EPU, SOCSO and JTK. In this exercise, may be not all data needed for the reports available in the LMDW database. In order to furnish all the data, data source from other agency needed. May be in next exercise or project, ISMK will determine which agency involved.

Data Warehouse
To address the issues of collecting, filtering and managing data from multiple sources and registers, we recommend the implementation of a data warehouse to hold the Labour Market Information. The design of the data warehouse is based on multiple meta-data formats available from each of the various data sources. The establishment of a data warehouse facilitates management and governance over the quality of data by the data quality assessment framework as shown in the following diagram.

Data from multiple sources and registers can be stored within a single Data Warehouse System provided that the data source and date is identified. Since different sources and registers store different data parameters, the data in each record may differ in content as indicated in the following where data from SOCSO (which is more timely, being updated monthly, but lacking in many employee parameters) is kept alongside data from NER submissions (which is less timely being collected on bi-annual basis, but rich in employee analytical parameters). By keeping data from multiple sources together in the data warehouse, availability and accessibility of data is ensured. This is shown in the following diagram

Data Aggregation Design
To support data originating from multiple sources or registers, the data warehouse needs to be designed to store two broad types of data: * Aggregated and summarized data – such as industry indices and statistics, as well as aggregated employer and employee data where individual employers and employees are not identified by any key identifier such as aggregates for all employees employed by a particular employer. Data to be stored in the
aggregated area, for example * Data from Economic Census

* Data from Business Tendency Surveys
* Data from Industrial Production Indices
* Statistics on Industries
* Detailed data identified by individual key identifiers – such as data on individual employers identified by their business or company registration numbers, and data on individual workers identified by their National IC numbers or household reference numbers. Data to be stored in the detailed area are, for example * Data NER data collection forms

* Employer and employee data from SOCSO
* Employer and job applicant data from JobsMalaysia
The distinction between aggregated data storage and detailed data storage is shown in the following diagram

Data Warehouse Design
In line with the data aggregation design, data to be stored in the data warehouse can be categorized into the following types of storages:

* Aggregated statistics – these will store data from economic census, broad-based surveys, industry production indices and other statistics * Detailed employer data with individual key identifiers – these will employer data from NER responses, JobsMalaysia registration and updates, and SOCSO registration and updates. Individual employers will be identified by their business or company registration numbers, and these will be linked and cross- referenced to employee data in order to establish the employer-employee linkage * Aggregated employee data – employee data collected from through the NER responses does not identify each individual employee. Rather, employee data is collected in aggregate by each employer. A separate data storage area is needed for this type of data as opposed to situations where data on individual employees are kept. However, the aggregated data still needs to be cross-referenced and linked to the respective employers. * Detailed workers data identified by National IC numbers – these are collected via SOCSO and the JobsMalaysia Portal. *
Detailed workers data represented by household heads and contents identified by household reference numbers – these are also detailed data on individuals, however they are identified by a different key identifier Stages of Data Storage

* The Data Warehouse exist in a chain of systems in which data is processed in stages to ensure conformity with the data assessment framework. These stages of data storage preceding the ultimate destination of the data warehouse is as follows * Data feeder stage – at this stage, data is captured and stored in their own areas or databases before being fed into the data warehouse pipeline. These may consist of * Data entry applications – these may be used, for example, for data entry from the survey responses forms. * Spreadsheets, text files and other forms of file-based data – these can be imported using data import applications into the data warehousing pipeline. These data may consist of industrial statistics, and indices. * Data from other databases – where data is already stored in other databases, such as SOCSO or JobsMalaysia, it may be extracted by specialized application into the data warehousing data pipeline * Data Staging Stage – data from the data feeder stage is fed into the data staging area for further processing before they are channelled into the data warehouse. Processing is carried out to filter, codify and transform (which may involve the use of applications such as a data editing application to codify non-coded parameters, such job position and industry category for SOCSO) in the incoming data for the following purposes * Ensuring coherency and compliance with data format standards, for example numeric formats for the National IC number. Data format standards that may apply include * Format of National IC number

* Format of Business/ Company Registration Number
* Format of all date data – days not exceeding maximum days of the month, months not exceeding 12 * Format of names – no numbers or special characters like exclaimation and question marks * Ensuring cross-interpretability and compliance with data categorization standards – for example, compliance with industry categories with the MSIC * Categorization standards that apply have been covered in section 8 and
includes * Towns, States and Countries

* Genders
* Job Positions
* Levels of Education
* Industry categories
* Ensuring timely data where stale or old data (based on their dates) entering the system may be filtered out at the data staging area, for example where data for SOCSO submissions from last year is inadvertently fed into the system * Ensuring accuracy of data – some obviously inaccurate data that may inadvertently enter the system (such as wrong birthday dating more than 100 years old, negative numbers for salaries, etc) may be filtered automatically using data quality rules applied at the data staging area * Producing calculated data – for example, monthly SOCSO submissions do not provide data on the employees exact salary. However, an estimate of the salary can be made based on the SOCSO contribution amount and the SOCSO contribution table. The process of calculating the estimate can be carried out at this stage. This ensures that all relevant data is produced to add value to the Labour Market Information data warehouse. * When data is cleansed, it is updated into a Historical Data Warehouse where all cleansed data is archived. The purpose of a historical archive in Data Warehousing is provide * A history of information for trending and time-series analysis * An audit trail of changes made to the latest status for future reference and data reconstruction * Snapshots of the latest data is taken from the Historical Data Warehouse to represent the latest status of the labour market. These are stored in the Snapshots Data Warehouse and updated from time to time. This activity add breadth and depth to ensure that relevant data is presented for decision-making. For example, SOCSO data on an employee that is updated regularly every month gives a monthly update on the employee income level. However, that data does not provide in-depth parameters about the employee such as education level.If data for the same person is found in JobsMalaysia (assume that the employee had registered as a job-seeker), then the monthly SOCSO data can be augmented with the JobsMalaysia data. This is how the process of acquiring snapshots is carried out to ensure that all relevant data is made use for
the Labour Market Information. These stages are shown in the following diagram

Updating of Snapshot Data
Data in the Snapshot Data warehouse reflects the latest status on an employer or employee based on the total historical data available in the Historical Data Warehouse. This snapshot is updated from time to time as new data is accepted into the Historical Data Warehouse. Various rules need to be formulated for the purpose of extracting historical data into the Snapshot Data Warehouse. Where detailed data on individual employer or employee is kept in the Snapshot Data Warehouse, this data should represent the latest available parameters for the specific employee or employer as collected from various sources. This illustrates clearly the use of key identifiers to identify individual employers and employees. Where Historical Data Warehouse is updated with the data on an individual employer or employer, the updating rules check against the Snapshot Data Warehouse whether there is an existing record for the employer/ employer. If there is an existing record, the appropriate parameters available from the latest historical data is updated. Where there is no existing record, a record for a new employee/ employer is created. This is shown in the following diagram

This manner of processing ensures that data from multiple sources that is relevant to monitor and perform insightful analysis on the Labour Market is utilised in the Data Warehouse for maximum relevancy. It also ensures that the most timely data from historical data available is utilized as a priority. Marking Stale Data

Apart from guarding data quality at the incoming stream, data quality in the storage area also needs to be monitored from time to time against staleness. various data rules need to be implemented to flag and invalidate (invalidated data is not deleted, but rather flagged, so as not to lose out on the value of historical data – which will be lost in the case of deletions). Depending on the date of data updates, data may be flagged as suspect and not be used in the latest snapshot. For example, if the latest SOCSO contribution data from an employee is dated Dec 2000, it is always a
certainty that the data on the employeee is outdated vis-a-vis his/her present situation. Data may also become stale with new to the referred standards e.g.. MASCO, MSIC and ILO classifications. In these cases, existing data will need to be remapped to the new standards, while new data will use the new standards. The remapping is necessary to ensure that existing data is comparable with new data as well as with the new standards. Some of the remapping exercise may be done automatically while some may require manual re-classification if the criteria cannot be programmed automatically. For the later case, the original data need to be retained for reference purposes. Other data rules that may applied include the omission of data in the incoming data stream. As such this is not a check against data that is incoming, but rather a check against data that is expected to be incoming but does not come in as expected. For example, a company that continues to make monthly SOCSO contributions drop some employees from its contribution list. If this persists for a few months, it may be treated as the employee had left the employer. Thus the workers and employers data in the Data Warehouse need to be updated accordingly. This act of ensuring data timeliness against data already held in storage is shown in the following diagram

Data Security
Permissions and Privileges
The data warehouse should enable different users or groups of users to be able to see different data depending on the permissions allowed to them. For example, detailed data containing information on individual employers and employees may be considered too confidential to be viewed by most users. Thus, most uses will be able to see aggregated data about employers and employees but not to see data regarding individual employers and employees.

Encryption
Non-reversible encryption algorithms (also known as One-Way Encryptions) may be used to scramble data used to identify particular employers or employees. The same employer or employee will always produce the same scrambled data, but the scrambled data cannot be used to find out the true identity of the employer or employee.

Usage of Data In The Data Warehouse
The sampling, analysis and extrapolation purpose will use data warehousing and data mining tools present in the data warehouse, which may be augmented with end-user statistical tools) to form a market picture using the following techniques * Summarization – data from the data warehouse is aggregated and summarized alongst multiple dimensions (e.g., tie, location, industrial sector, education etc – a comprehensive list was covered in Section 9) – produce insightful information about the status and trends in the market. In summarizing the data, not all data will be totaled, some such as age would be averaged, while others may use the median. * Slice and Dice – data from the data warehouse may be viewed from many angle and combinations of angles. Thus employee data may be viewed by employee parameters such as age and gender, and employer data may be viewed by employer parameters such as industry and size of paid-up capital. Combining the employee and employer parameters using slice-and-dice enhances the ability to analyse data , so one may ask questions such as ‘How are employers in various sectors and of various sizes employing workers of various age groups and genders?’ * Clustering Analysis – is a study of correlations and tendency of members or items being studied to cluster around sets of apparently related parameters. For instance, it is generally assumed that an increase in economic growth and production causes a corresponding increase in labour demand. However, recent economic studies undertaken in many developed countries has shown signs of a weakening in this correlation. The ability to perform clustering analysis enables the discovery of new correlations and to test existing assumptions. data mining tools using the data warehouse generally allow automatic discovery of clusters. * Cyclical Analysis – the historical archive of the data warehouse enables analysis and monitoring of cyclical behaviours in the Labour Market. Cycles may be broken-down into sub-cycles and different cycles may be compared to determine the impact of one cycle against the other. * Trend Anlsyis – is allowed using various tools such as moving averages, monitoring trend lines against the historical data warehouse. Combined with the ability to slice and dice the data, trends may be analysed in particular niches of the Labour Market such as gender, industrial sector,
age group, ethnicity etc. * Correlation study – can be conducted against the data base using various tools such as chi-squared and other methods to determine the correlation between various parameters and the strengthening or weakening of influential forces on the cause and effect relationships within the labour market. By using these tools against the data warehouse, the ability to form an updated perspective on the Labour Market becomes less tedious and can be performed more regularly and comprehensively due to the easy access to pre-cleansed and standardised data.

Benefits of Data Warehouse
Data from the Historical and Snapshot Data Warehouse which is cleansed, codified and transformed in the Data Staging stage will not contain workers data from the entire population of the country. That is because, the scope of the data sources (as evaluated in Section 9) does not cover the entire population. However, there is data from the administrative data will provide valuable augmentation and add value to existing survey and census data for the formation of a data warehouse ffrom which statistical sampling, analysis and extrapolation can be done to form a picture of the entire Labour Market. From the perspective of the Data Quality Assessment, the data in the data warehouse had passed the following tests * Relevance – as much relevant data had been stored from multiple sources and registers in the data warehouse. These have been combined using individual key identifiers wherever available to ensure that data relevant to each employer and employee is attached to the individual. * Accuracy – data in the data warehouse had been checked for accuracy against corrupted data during data staging such as excessive age. Identifiying employers and employees using key identifiers ensure an important rule of accuracy is enforced – that is against double counting. * Timeliness – incoming data is checked against staleness (by date of data) and historical data is extracted into a snapshot according to the latest data item. Data stored in the Snapshot Data Warehouse is checked from time to time against staleness and suspect data is flagged against use. * Interpretability – to ensure adequacy of interpretability, data from multiple sources and registers with each’s own strengths and weaknesses is combined in the data warehouse to give the widest latitude and range of parameters for interpretation. To ensure
consistency in interpretations, incoming data during the Data Staging stage is checked and codified against standard categories as detailed out in Section 8. * Coherence – the ability to check data for coherency comes with the storage and comparability of data from multiple sources. It is also achieved against a historical time-series to ensure consistency of trends and cyclical fluctuations. The data warehouse enables the achievement of this goal by storing data from multiple sources and registers, and keeping an archive of historical data. * Accessibility – having a data warehouse ensures maximum accessibility to cleansed, standardized, analytical data. References

Main references was made to the following standards for the purpose of determining the indicators required and for the classification of data

References was made to other sources from the Department of Statistics, the Economic Planning Unit, the Ministry of Education and the Ministry of Higher Education, Malaysia, such as * National Population Census (DoS)

* Labour Market Survey (DoS)
Apppendix 1 – Summary
Appendix 2 – Data Assessment
Appendix 3 – Data Collection Forms

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