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The effects of unemployment in the UK Essay

Chapter 1: Introduction

A brief introduction to the topic will be displayed in order to educate on the general information surrounding the topic. Overview -The study is being undertaken to reveal if unemployment rates affects the amount of crimes committed. The study also intends to show how unemployment rates cause an increase or decrease in certain criminal activity. This research can be of great importance as it will highlight the motives behind crimes and will show the extent of the problem in each category of crime with relation to unemployment rates. This research can be used to educate readers on how serious the issue is and what can be done to improve it. Purpose-The purpose of this study is to acquire knowledge to address the issue of unemployment rate related crime and the type of crime that unemployment causes. The use of quantitative research will try and fulfill that purpose by answering questions and testing the hypothesis.

Research questions:

* To what extent does unemployment influence rates of crime? * What certain criminal activity is affected by increased rates of unemployment? * What can be done to reduce crime related to unemployment? Hypothesis – Increased unemployment rates in the UK will cause an increase in criminal activity with the biggest increase in burglary and theft related crime due it to causing a motive to act out a criminal offence.

Chapter 2 : Literature Review

It cannot be denied that the seminal paper by Becker (1968) and Ehrlich (1973) have been considered as the most important work in rejuvenating the interest in crime studies. While Becker (1968) emphasizes on the cost and benefit of crime, Ehrlich (1973) extends Becker’s crime model by including the role of opportunity cost between illegal and legal work. Poutvaara and Priks (2007) examine a model of criminal gangs and suggest that there is a substitution effect between property crime and violent crime. They further explained that unemployment increases the relative attractiveness of large and less violent gangs engaging more in property crime.

Papps and Winkelmann (1999) found some evidence of significant effects of unemployment on crime both for total crime and for some subcategories of crime in their analysis that covered sixteen regions over the period 1984 to 1996 in New Zealand. Narayan and Smyth (2004), in their study on Australia, employing Granger causality test, to examine the relationship between seven different categories of property crime and violent crime against the person, male youth unemployment and real male average weekly earnings from 1964 to 2001 within a cointegration and vector error correction framework.

It is found that fraud, homicide and motor vehicle theft are cointegrated with male youth unemployment and real male average weekly earnings. However, there is no evidence of a long-run relationship between either break and enter, robbery, serious assault or stealing with male youth unemployment and real male average weekly earnings. On the contrary, Habibullah and Law (2007) also utilized Vector Error Correction Model (VECM) in their study about crime and financial economic variables in Malaysia, and generally their result suggests that criminal activity in Malaysia cannot be explained properly by real income per capita, financial wealth and interest rate.

In another related paper, Baharom and Habibullah (2008) found that crime exhibits neither long-run nor short run relationships with income inequality and they are not cointegrated. In contrary Habibullah and Baharom (2008) employing bounds test (ARDL) found that in the long-run, strong economic performances (real income per capita) indeed have a positive impact on murder, rape, assault, daylight burglary and motorcycle theft, while on the other hand, economic conditions have negative impact on armed robbery.

Chapter 3: Methodology

Approach and Research design – This section of the methodology will begin by explaining why the research into unemployment related crime within the UK is of importance. Firstly, the specific topic area is lacking in previous study or research when referring to the UK in specific. It may then highlight the effect that unemployment rates have on a certain type of criminal activity and provide an insight to the extent of the problem. This could have a profoundly positive effect on the reasons behind the crime and what needs to be done to reduce unemployment related crime. Statistics on crime are important to inform policy and decision making; to facilitate democratic accountability; and to allow the public to assess risk of crime in their neighbourhoods.

Data collection – This section of the methodology will briefly inform the reader of the general details of the data collection, including all the sources. Data collection for crime rates will be collected from official secondary sources. The UK crime statistics are collected from three different sources. The crime data for England and Wales will be collected from the official Home Office website in the research and developments section. Data for Scotland will be collected from the Scottish Governments Website under publications area. Finally the data for Northern Ireland will be collected from the crime statistics page at the website of the Police Service of Northern Ireland.

England and Wales-
Scotland –

Northern Ireland – The rate of crime will resolved by dividing the number of crimes by the population then multiplied by 1000. This will give the number of crimes committed per 1000 people, a common crime rate measurement. In order to obtain the UK population data the most official and precise source will be used, this being the World Bank – The unemployment rate is a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labour force. Data for unemployment rates will be collected from an official source.

The Office of National Statistics will be used-

Statistical analysis of the data collected from the sources will be carried out to discover the relationship between crime and unemployment rates using SSPS. Then further statistical analyse will be performed to reveal the relationship between unemployment rates and types of crimes committed. These statistical tests will be indentified and explained within this section of the methodology.

Chapter 4: Results

This section of the project report will be used to show key results drawn from the secondary data that will be included in the appendices. The Data will be organized data into tables and graphs where appropriate. The data displays that when unemployment rates increase so does the crime rates. This trend can be seen to continue when comparing most annual unemployment rates and crime rates. The data will be compared and contrasted in further detail during the course this section. Results on unemployment rates and types of crime committed will also be compared and contrasted. Increases in theft and burglary can be seen to increase with increased unemployment rates. A slighter increase of other crimes such as violence and sexual assaults can also be seen. Any anomalies found within the data will be displayed.

Chapter 5 : Discussion

From analyse of the results it is clear to see that levels of crime increases with increased unemployment rate. It may be argued that unemployment causes a variety of motives to commit a criminal offence. The biggest motive is a need to make money due to the fact that unemployed people receive no income apart from benefits if received at all. The results are clearly evident of this with a large increase in burglary and theft with the increase of unemployment. Crime might be the only way people see themselves bringing in money to keep their residence and feed them.

Both crime and unemployment are factors that when left uncontrolled can produce devastating problems for individuals that ultimately affect the entire economy. Developing this relationship between crime and unemployment and emphasizing its importance is necessary for subsequent policy formation. However, it is more important to identify the linking factors in this relationship than it is to define the relationship itself.

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