1) The elasticity of one variable with respect to another between two given points. It is used when there is no general function to define the relationship of the two variables. Arc elasticity is also defined as the elasticity between two points on a curve. The P arc elasticity of Q is calculated as
The percentage is calculated differently from the normal manner of percent change. This percent change uses the average (or midpoint) of the points, in lieu of the original point as the base.
2) Definition of ‘Law of Diminishing Marginal Returns’
A law of economics stating that, as the number of new employees increases, the marginal product of an additional employee will at some point be less than the marginal product of the previous employee.
The law of diminishing marginal returns means that the productivity of a variable input declines as more is used in short-run production, holding one or more inputs fixed. This law has a direct bearing on market supply, the supply price, and the law of supply. If the productivity of a variable input declines, then more is needed to produce a given quantity of output, which means the cost of production increases, and a higher supply price is needed. The direct relation between price and quantity produced is the essence of the law of supply.
An economic theory that states as additional inputs are put into production, the additional return will be in successively smaller increments. This can be due to crowding, adding less appropriate resources or increasing inputs of lower quality.
In More Laymen Terms
As the saying goes, “Too Many Cooks Spoil the Broth,” in any production there is a point of diminishing returns where just adding more inputs will not give the same income as it once did. Although many industrial firms strive to reach ‘scale,’ where their size gives them a cost advantage at higher production levels, no matter what industry a firm finds itself there will always be a point where the additional gain from added input is reduced.
3) The prisoner’s dilemma is a canonical example of a game analyzed in game theory that shows why two individuals might not cooperate, even if it appears that it is in their best interest to do so. It was originally framed by Merrill Flood and Melvin Dresher working at RAND in 1950. Albert W. Tucker formalized the game with prison sentence payoffs and gave it the “prisoner’s dilemma” name (Poundstone, 1992). A classic example of the prisoner’s dilemma (PD) is presented as follows:
Two men are arrested, but the police do not possess enough information for a conviction. Following the separation of the two men, the police offer both a similar deal—if one testifies against his partner (defects/betrays), and the other remains silent (cooperates/assists), the betrayer goes free and the cooperator receives the full one-year sentence. If both remain silent, both are sentenced to only one month in jail for a minor charge. If each ‘rats out’ the other, each receives a three-month sentence. Each prisoner must choose either to betray or remain silent; the decision of each is kept quiet. What should they do?
If it is supposed here that each player is only concerned with lessening his time in jail, the game becomes a non-zero sum game where the two players may either assist or betray the other. In the game, the sole worry of the prisoners seems to be increasing his own reward. The interesting symmetry of this problem is that the logical decision leads both to betray the other, even though their individual ‘prize’ would be greater if they cooperated.
In the regular version of this game, collaboration is dominated by betraying, and as a result, the only possible outcome of the game is for both prisoners to betray the other. Regardless of what the other prisoner chooses, one will always gain a greater payoff by betraying the other. Because betraying is always more beneficial than cooperating, all objective prisoners would seemingly betray the other.
In the extended form game, the game is played over and over, and consequently, both prisoners continuously have an opportunity to penalize the other for the previous decision. If the number of times the game will be played is known, the finite aspect of the game means that by backward induction, the two prisoners will betray each other repeatedly.
4) Third degree discrimination involves charging different prices to different segments of customers. This method of price discrimination is really an imperfect variation of the perfect type represented by first degree price discrimination. In this method different segments of customers are identified and each segment is charged price base on what price is most profitable for the company in each segment. The most common way of segmentation for this type of price discrimination is by geographic location. A very prominent example of this type price discrimination is charges for operations by surgeons. For the same type of operations surgeons and hospitals charge different fees depending on the type of hospital room and other facilities that the patient chooses during hospitalization for operation. Other common forms of such price discrimination include discounts such as those for students or senior citizens.
CASE LET 1
1) Demand theory indicates that the determinants of consumption are income (I), the price of the good in question ( pi ), the prices of other goods ( po ) and other variables such as tastes: i i q q ( i o I, p , p , other variables).
Consider the case of an illicit commodity such as marijuana. The consumption of marijuana involves risks of fines, in some cases imprisonment and, possibly, other costs associated with the shame of being caught. Consequently, the price of marijuana in its demand function ( p ) m should be interpreted as being made up of the conventional money cost ( p ) mplus the expected “other costs” per unit:
2) Legalization of marijuana would eliminate the criminal sanctions and penalties associated with its consumption. As this would decrease the “full” price, consumption would be expected to rise. Marijuana consumption is significantly higher amongst males than females – 60 percent of all males have consumed it, compared to 46 percent of all females. Consumption of marijuana is estimated to increase by about 4 percent if it were legalised; and by about 11 percent following both legalisation and a 50-percentfall in its price. Price is a significant determinant of marijuana consumption. Whilst marijuana consumption is estimated to be price inelastic, estimates of most of the price elasticities are significantly different from zero.
Two types of price elasticities of demand for marijuana were estimated, gross and net. The gross price elasticity includes the effects of both legalisation and a price change, while the net version excludes the legalisation effect. The price elasticity of demand for marijuana differs significantly with the type of consumer. For more frequent users (daily, weekly and monthly), gross and net price elasticities are estimated to be -.6 and -.4, respectively. Occasional smokers having a gross price elasticity of about -.3 and net elasticity of about -.1. Regarding those who are no longer users, they have gross and net price elasticities close to zero. For a given type of consumer, males and females share the same elasticity value.
CASE LET 2:
1) In my opinion Yes, the Indian companies are running a major risk by not paying attention to cost cutting. To illustrate Comparing major Indian companies in key industries with their global competitors shows that Indian companies are running a major risk. They suffer from a profound bias for growth. The problem is most look more like Essar than Reliance. While they love the sweet of growth, they are unwilling to face the sour of productivity improvement. Nowhere is this more amply borne out than in the consumer goods industry where the Indian giant Hindustan Lever has consolidated to grow at over 50 per cent while its labour productivity declined by around 6 per cent per annum in the same period. Its strongest competitor, Nirma, also grew at over 25 per cent per annum in revenues but maintained its labour productivity relatively stable. Unfortunately, however, its return on capital employed (ROCE) suffered by over 17 per cent.
In contrast, Coca Cola, worldwide, grew at around 7 per cent, improved its labour productivity by 20 per cent and its return on capital employed by 6.7 per cent. The story is very similar in the information technology sector where Infosys, NIIT and HCL achieve rates of growth of over 50 per cent which compares favorably with the world’s best companies that grew at around 30 per cent between 1994-95. NIIT, for example, strongly believes that growth is an impetus in itself. Its focus on growth has helped it double revenues every two years. Sustaining profitability in the face of such expansion is an extremely challenging task What makes this even worse is the Indian companies barely manage to cover their cost of capital, while their competitors worldwide such as Glaxo and Pfizer earn an average ROCE of 65 per cent. In the Indian textile industry, Arvind Mills was once the shining star. Like Reliance, it had learnt to cook sweet and sour.
Between 1994 and 1996, it grew at an average of 30 per cent per annum to become the world’s largest denim producer. At the same time, it also operated a tight ship, improving labour productivity by 20 per cent. Despite the excellent performance in the past, there are warning signals for Arvind’s future. The excess over the WACC is only 1.5 per cent, implying it barely manages to satisfy its investor’s expectations of return and does not really have a surplus to re-invest in the business.
Apparently, investors also think so, for Arvind’s stock price has been falling since Q4 1994 despite such excellent results and, at the end of the first quarter of 1998, is less than Rs 70 compared to Rs 170 at the end of 1994. Unfortunately, Arvind’s deteriorating financial returns over the last few years is also typical of the Indian textile industry. The top three Indian companies actually showed a decline in their return ratios in contrast to the international majors.
2 ) Fast moving consumer goods will become a Rs 400,000-crore industry by 2020. A Booz & Company study finds out the trends that will shape its future
Consider this. The anti-ageing skincare category grew five times between 2007 and 2008. It’s today the fastest-growing segment in the skincare market. Olay, Procter & Gamble’s premium anti-ageing skincare brand, captured 20 per cent of the market within a year of its launch in 2007 and today dominates it with 37 per cent share. Who could have thought of ready acceptance for anti-ageing creams and lotions some ten years ago? For that matter, who could have thought Indian consumers would take oral hygiene so seriously?
Mouth-rinsing seems to be picking up as a habit — mouthwash penetration is growing at 35 per cent a year. More so, who could have thought rural consumers would fall for shampoos? Rural penetration of shampoos increased to 46 per cent last year, way up from 16 per cent in 2001. Consumption patterns have evolved rapidly in the last five to ten years. The consumer is trading up to experience the new or what he hasn’t. He’s looking for products with better functionality, quality, value, and so on. What he ‘needs’ is fast getting replaced with what he ‘wants’
Categories are evolving at a brisk pace in the market for the middle and lower-income segments. With their rising economic status, these consumers are shifting from need- to want-based products. For instance, consumers have moved from toothpowders to toothpastes and are now also demanding mouthwash within the same category. The trend towards mass-customization of products will intensify with FMCG players profiling the buyer by age, region, personal attributes, ethnic background and professional choices. Micro-segmentation will amplify the need for highly customized market research so as to capture the specific needs of the consumer segment targeted, before the actual product design phase gets underway.
3) Industies impressive growth in value added as observed in the previous sub section is not accompanied by a commensurate rise in the level of relative productivity in terms of the cross–country analysis. The fragmented nature of Indian pharmaceutical sector characterized by the operation of a very large number of players, estimated to be about 10,000 units of which just 300 units are medium and large sized7, may be a reason for low level of productivity. The other important factor for low productivity can be due to the nature of technological activities in the sector, which tends to rely more on process than product development. Further, it may be that Indian companies are focusing at the low end of value‐chains in the pharmaceuticals like producing generics than opting for branded products or supply bulk drugs to global players than market formulations of their own.
4) The Indian textile industry has been one of the foremost contributors to the country’s employment, exports, and GDP. The industry has been rated as one of the key drivers of the Indian economy and a bold target of exports of $50 billion (currently it’s $22 billion) had been targeted by the year 2012 by the government after the dismantling of the quota regime in 2005. However we are still far away from that target.
Though now it can be blamed on the worldwide recession, I think we need to do some soul searching as to was it anyways possible. Globally, the Indian industry is recognized for its competitive advantages, especially in the cotton segment. The government has set huge targets for the industry and expects to attract investments of about Rs 1.5 lakh crore during the eleventh Plan period. This would meet the export and domestic targets, while taking various initiatives like setting up textile parks, training centers, and ‘made in India label promotion’ to global markets.
The Indian textile industry is facing tough competition in the US, as exporters from smaller countries like Bangladesh are cornering the lucrative market at a faster pace, a FICCI study said. “In addition to China, countries like Indonesia, Vietnam and Bangladesh have managed to perform better than India in the US market in 2009,” the study said. Bangladesh, Indonesia and Vietnam managed to increase their share in the US textiles and apparel import in 2009 year on year at a faster rate than India.
The Indian textile industry will no doubt survive and move along by the strengths of its traditional position and domestic market. However, the growth envisaged and it being re-classified as sunshine industry over the last three years from a sunset industry may turn out to be a myth
1) A vision of the impact of free trade can also be gleaned from Nobel Prize winning economist Paul Samuelson (1970) who confidently asserted that: Free trade promotes a mutually profitable division of labour, greatly enhances the potential real national product of all nations, and makes possible higher standards of living all over the globe.
It promotes a regional division of labor — this means that some regions of the world (or countries) will specialize in certain things. They will specialize in areas where they have a comparative advantage.
It enhances national production — this means that countries will be able to produce more things if there is trade. That is because they focus on producing things they are good at and do not waste resources on things that they are not good at.
It allows higher standards of living because there is more production. If there is more production, there are more things available to be consumed.
Another belief in the importance of free trade can be ascribed to its perceived indirect effect on peace, security and the prevention of war. One of the first articulations of this is by Baron de Montesquieu, who writing in 1748, stated: Peace is the natural effect of trade. Two nations who traffic with each other become reciprocally dependent; for if one has an interest in buying, the other has an interest in selling, and thus their union is founded on their mutual necessities. This theory of mutual interdependence has been explored in some detail by authors such as Keohane and Nye67 and is echoed in attempts to build and protect the mandates of global institutions seeking such co-operation. However few attempts are made to track the results of policy activities on whole population of States, and as a result the overtly negative impact on some groups, usually minorities and indigenous
2) The Decision Trees, used to help with decision making in business ( and many other areas), are a form of diagrammatic analysis. They are used as a tool for helping managers to choose between several courses of action. They provide an effective and clear structure for presenting options and within decision trees the probabilities and financial outcomes of these options can be measured. They also help to form a balanced picture of the risks and potential financial rewards associated with each possible course of action.
In many business decision making situations chance (or probability) plays an important role, and the use of decision trees helps build probability into the decision making process. Pictorial representation of a decision situation, normally found in discussions of decision-making under uncertainty or risk. It shows decision alternatives, states of nature, probabilities attached to the state of nature, and conditional benefits and losses. The tree approach is most useful in a sequential decision situation. For example, assume XYZ Corporation wishes to introduce one of two products to the market this year. The probabilities and present values (PV) of projected cash inflows follow:
A decision tree analyzing the two products follows:
Based on the expected net present value, the company should choose product A over product B.