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The reasons behind regional unemployment differentials

This essay will look at the reasons behind regional unemployment differentials, looking at various theoretical explanations as to why these differences may occur. The two main theoretical accounts that will be looked at are the disequilibrium theory and the equilibrium theory. Within the equilibrium theory there are two models incorporated, the amenity and the matching models, which are used to explain reasons behind unemployment differentials. I will then focus on several pieces of empirical evidence to justify these theories, and give a more realistic analysis into why and how these disparities transpire.
Unemployment rates vary across both time and area, this essay will seek to understand some of the reasons behind these varying differences between regions. Unemployment differences are affected due to various factors, these can be in the form of basic household decisions, business decisions, wage flexibility and decisions that inevitably effect migration and labour force participation. These forces will have a positive or negative effect on the unemployment rate either increasing or decreasing disparities between regions. These two conflicting theories that will be looked at in detail can help explain why unemployment varies from region to region.
Theoretical explanations Disequilibrium Theory This classical theory states that regional unemployment differences are temporary; it assumes that given enough time, the unemployment rate will adjust to equalisation across space. Unemployment can then be reduced through inter-regional migration, the movement between two or more regions having an effect on a regions unemployment rates bringing them closer together. The problem however is that the theory states that these equilibrating forces are weak and the process of adjusting to equilibrium may be slow, so substantial unemployment differences between regions may persist for longer periods of time. A reason for it persisting may be due to a shock that raises unemployment locally, for example if a region experiences a factory closure. However, there are several factors that effect the speed of adjustment, one of the main reasons is the flexibility of households and firms, Household/institutional inflexibility slow down regional convergences. Where they are more flexible, the adjustment process will be faster. An example of this flexibility in relation to inter-regional migration decisions could be where an individual chooses to move to an area where the likeliness of successful employment is higher, or a firm basis its decision to set up business in an area that offers a larger pool of labour They do not however react as quick as households as the decision to move is costly and less easy to reverse causing reluctance.
The forces that are seen to be weak that affect the speed of adjustment include migration, capital flows and the flexibility of wages, but these forces are also dependent on sub factors that could influence the speed of adjustment on both the labour demand and labour supply sides. These factors include aspects such as age, education, unemployment benefits, crime, demand and supply shocks etc. Looking at age, it is usually agreed upon that younger people are more likely to move as they have a lower opportunity cost of migrating therefore less risk. If the unemployment rate is high in one region that has very few young people, this then allows us to conclude that the fall in unemployment is unlikely to fall quickly [1] . Alternatively if we look at young adults that live with their parents at home, for them the risk and cost is much higher of moving out with the stress of finding a new home and managing costs etc. Educationally, this can have a huge effect on individuals migrating decisions and employment opportunities. Better educated workers are more likely to move in response to economic opportunities thus raising their chances of finding employment. The labour market for skilled workers is also much bigger allowing for an easier job search that may bring greater result in attaining a job. McCormick and Sheppard backed this by finding that regions with a larger proportion of less skilled workers are likely to suffer higher levels of unemployment [2] .
A higher level of education also gives an individual better job information, giving him/her higher possibilities of finding jobs elsewhere. Higher educated workers are also said to have less psychological unwillingness to re-locate, especially if it meant to pursue further studies or for career advancement (Gabriel et al).
Other factors that can affect a regions speed of adjustment can include whether living in a rural or urban setting. Living in a more rural area may mean that adjustment may be much slower to that of an urban area. If a factory was to shut down in an urban area, workers can apply the same skills to a nearby factory allowing for an easy transition from one job to another without moving. Labour mobility would be higher if the cost of moving was cheaper, but in most cases the costs are very high. These costs can be from basic transport costs from one area to another to most importantly housing market prices relative to the time of migration etc. Unemployment rates will also converge at a slower rate if unemployment benefits are generous, thus meaning that the pressure to find a new job is reduced by a great amount as there is less stress to go out and seek employment.
Disequilibrium theory offers an explanation for regional unemployment differences and how forces affect the adjustment process in relation to equalisation. The next theory offers an explanation that looks at unemployment on a more individualistic level based on preferences.
Equilibrium Theory Equilibrium theory or equilibrium unemployment reflects the workers preferences for certain areas [3] ,
another way of describing this situation could be in terms of job search. This theory expects out migration from regions that experience high levels of unemployment, thus accepting the concept of free mobility. Each region is seen to be at its natural state of unemployment where the national rate of unemployment is determined by each region compensating its attractiveness to workers, or in other words reflecting its regions favourable services or comforts. Regional unemployment disparities exist in this theory of equilibrium unemployment, thus expecting out migration in order to seek employment, however some individuals decide to stay in areas of high unemployment. This inclination to stay must be compensated in some way to induce them to stay voluntarily. The three main compensating factors are attractiveness of amenities, high wages and high unemployment benefits. The unemployed will not work for lower than expected wages, this is because the benefits of seeking for a job outweigh the low wages that are on offer. This then results in the wage rate failing to clear the market at completely full employment. Another determining factor in the search for employment is an individuals or households preference for certain living areas.
Within equilibrium regional disparities two models have emerged, the amenity and matching models. The amenity model considers regional variation in job opportunities to be essentially compensating in nature [4] . The matching model introduces costs into the framework.
The Amenity Model This model works on the assumption that households are free to move between regions. Households will migrate to certain areas based on the attractiveness of living conditions or amenities, e.g. climate, public services, transport, education. Firms also expand business in areas that present encouraging conditions for example a solid infrastructure and a healthy available amount of natural resources. Migration occurs up until the point where utility or profits have been eliminated from that particular area.
Firstly we consider a household that is mobile between regions. The utility function of this household can be written as U=f(w,ur,a), where utility is a function of regional wage rate (w), regional unemployment rate (ur) and regional household amenities (a). Regional wages and unemployment are linked by a wage curve that can be expressed as w= f(u). In relation to figure 1, the zero migration locus and the wage curve equally determine the equilibrium regional unemployment and wage rates as a function of the amenity level, equilibrium is when both the locus and wage curve intersect. Higher unemployment rates would have to be compensated for by a higher wage rate or better amenities, thus stopping households from moving. An increase in amenities (a) would cause a downwards shift of the locus no longer part of equilibrium, households then experience in migration until a new equilibrium is reached with higher unemployment and lower wages. Wages are flexible and workers can move between labour markets in response to better amenities on offer, which can result in permanent differences in the wage and unemployment rates. We expect wages to be lower and unemployment to be higher in areas where amenities are positive, divergence would only occur if the labour market does not clear in response to negative shocks. If the labour market did respond quickly, this would reduce labour demand reducing wages, resulting in out migration to places that offer higher wages. A reason for unemployment disparities could be due to negative demand shocks affecting particular regions. Regional unemployment differentials may persist due to differences in amenities, for example higher unemployment in regions with better climate and infrastructure etc, but amenities change slowly over time therefore unemployment differences are also going to move slower over time.
Figure 1 [5]
The Matching Model The amenity model assumes that the migration of households and firms are a response to differences in utility or profits for firms, the matching model introduces the concept of moving costs. At each period part of the workforce are made redundant, thus having to both leave the region and face the costs of moving or search for a job. As Unemployment rates increase, the labour market becomes more and more congested, therefore increasing the cost of searching for a job leaving it more profitable to migrate. Those who choose to stay enter the unemployment pool, where the probability of finding employment is a declining function of the regional unemployment rate. For equilibrium the flow of redundant workers is equal to the flow of workers leaving the unemployment stock, shown in figure 2. Regional unemployment and migration is dependant on the rate of job destruction within a region, the higher the job destruction the higher the unemployment rate therefore higher out migration is experienced.
Figure 2 [6]
A major influence on this is a regions industry mix, Regional job destruction is affected by a regions industry mix, where declining industries compete with fast growing industries. Backward regions with a poor industry mix will be seen as having high unemployment and a high rate of net out migration. This high level of regional unemployment is due to the congestion of the labour market in these declining regions that have poor industry structures. Fast growing industries can allow for the creation of new jobs, where a firm has open places for those who seek employment. Job creation is dependent on the information that is available to the potential workers, again highlighting that those better educated may be the ones who have access to this information. Job creation can come through government spending stimulating investing in projects or new services, through legislation and monetary policy or through the creation of new industries.
These two models have very differing policy implications. For the amenity model, government regional policies may not be very effective in reducing unemployment due to population movements and capital flows restoring equilibrium disparities. On the other hand, with the matching model, government policy may be able to reduce unemployment by stimulating and promoting fast growing industries in declining regions.
Empirical Evidence Green 1998 [7]
Green looked at regional unemployment disparities in the UK to gain a better understanding as to why unemployment rates vary between different geographical areas. His study examined unemployment rates for a sample of 10,000 areas in the U.K and used data from the census of the population. One of the main focuses was on what factors are most correlated with disparities. Greens findings were that between 50-60% of variation in unemployment rates between small areas in Great Britain can be accounted for the following factors; high unemployment in areas that had a high proportion of people with low income within that area or lived in rented accommodation, also poorly qualified individuals that live in large cities. Green found a distinct geographical concentration of those most at risk of becoming unemployed, and suggested the need for spatially discriminating policies in order to lower unemployment.
Taylor, Bradley (1997) [8]
Taylor and Bradley set out to investigate regional unemployment in Germany, Italy and in the U.K. Their findings discovered that two factors had a huge influence on regional unemployment differences. The first was that unemployment is higher in regions that show high labour costs, this finding was consistent with numerous studies such as studies by Bean (1994) and Cameron

The Challenges And Opportunities For India Economics Essay

“If the (India-Russia-China-Brazil) relationship progresses, then you basically have the world’s heartland- two billion people allied with a formidable technological power in Russia. That would be a disaster for the United States.”
Maynes [1]
CHAPTER 1 INTRODUCTION 1. The bipolar world has long ceased to exist and the world is now moving towards a multi polar world with emergence of various regional forums with common energy, economic, climate and trade agendas. One such forum which has attracted attention of leading economies is BRIC. The key players among the emerging economies are the quartet of Brazil, Russia, India and China popularly referred to as BRIC. The BRIC concept was first proposed by Goldman Sachs in 2003. It is estimated by experts that the economies of BRIC countries could outstrip the economies of G-6 countries in near future. BRIC with 40% of the world’s population and output is seen as the group which can alter the future of global economy. India being the largest democracy and one of the fastest growing economy has a definite role to play in the emerging world order with special reference to the BRIC.
2. The BRIC countries have consistently displayed high annual growth rates since 1980. BRICs share in the global economy has increased by 1.5% over the last decade. The rapid development of emerging economies and BRIC in particular, presents both opportunities and threats for sustained economic growth of India. It is almost nine years since Goldman Sach gave the term “BRIC” in its Global Economics Paper, “Building Better Global Economic BRICs”, published in 30 November 01. An short form for the economies of Brazil, Russia, India and China, the term was first significantly used in a Goldman Sachs report, which predicted that by 2050 these four economies would be wealthier than most of the current major economic powers. The forum has managed to increase its presence on the global stage in the past years and is countering the influence of western power in various forums. The BRIC nations are also looking in future for a more multi-lateral world and use the forum as a vehicle to pursue this aim. However as per studies carried out by many analyst doubts whether the BRIC concept has graduated from mere theory, to real, actionable practice?
3. As per studies carried out by economist, the BRIC thesis suggests that India and China would emerge as the world’s dominant suppliers of manufactured goods and services, respectively, while Brazil and Russia will become similarly dominant in supplying raw materials. As per the thesis evolved by Goldman Sachs, these countries are not only a political alliance or a formal business association but they have the potential to form a powerful economic bloc. Nevertheless, these countries have taken steps to increase their political co-operation on various international forums of trade and economics. [2]
4. The thesis put forward by Goldman Sachs [3] suggests that the economic potential of Brazil, Russia, India, and China is such that they could be among the four most leading economies by the year 2050. The thesis was proposed by Jim O’Neill, global economist at Goldman Sachs. These countries together encompasses almost 25% of the world’s land coverage and 40% of the population and hold a combined GDP of 15.440 trillion dollars. In fact, by the end of 2010, their combined GDP is already 15% of the global economy. China has overtaken Japan this year to become the second-largest economy in the world. The BRIC countries are among the biggest and fastest growing economies and emerging markets in the world. [4]
5. Brazil is the largest economy in Latin America and the eighth largest in the world, based on nominal GDP and ninth largest by purchasing power parity. Brazil is one of the fastest growing economies in the world with an average growth rate of 5 %. As per Goldman Sachs report Brazil will become one of the five largest economies in the world in the times to come, thus becoming one of the most sought after industrial destination. Brazil has a broad base in the sophisticated technological sector that ranges from automobile, petrochemicals, fertilizers, submarines, aircrafts, space research and also a pioneer in many fields, including deep water oil research, ethanol production and blending. In recent years India has realised the mutual trade potential of the two countries, which is evident from the frequent interaction of leaders from both countries.
6. The economies of China and India, whose recent growth has been triggered by foreign investment and exports of manufactured goods, are vastly different from resource-fuelled Russia and, to a lesser extent, Brazil. The opportunities among BRIC nations to further their economic co-operation are evident. Brazil and Russia in future will continue their leadership roles in developing and trading natural resources, while India and China will remain global players in manufacturing, services and technology sector. All four economies have recently bounced back from recession and are key players in sustaining the global recovery. As per the current trends, the group’s combined share in global GDP should reach 60 percent by 2050. The countries’ growing economic influence has turned BRIC into a major economic bloc in the new multi polar world order. [5]
7. India’s economic growth since independence in 1947 has been well below potential as compared to its population growth, hindered by low productivity. Tentative steps to reform the economy in 1985 and then fundamental reforms of 1991, has impacted the growth with economic growth averaging 6% annually. Since 2003, there has been a consistence increase in India’s potential growth to nearly 8% from 5%-6% seen in the previous decade. Growth in the productivity has been the key driver behind the progress in the GDP growth, contributing nearly 50% of overall growth since 2003. The drivers of growth are various sectors, important of which are agriculture, services sector and industry. Industry is increasingly becoming an important growth driver, contrary to general belief that India’s growth is services driven. Almost 25% of the services are directly related to industry, in the sectors such as trade, transport, electricity and construction. Recent jump in the productivity are in part due to a turnaround in industry productivity, which has transited from negative to positive cycle.
8. India’s current growth rates of about 8% have been achieved without much increase in domestic capital accumulation or FDI, raising the prospects that further increase in FDI could result in boosting further growth. India is well below its efficiency in the productivity frontier, due to inefficiencies in the production sector. However, services productivity has remained strong over the past decades. Labour has moved into industry from agriculture, at the same time capital has moved to services since 2002.
9. As per economists and experts, India will remain a low-income country for decades, with per capita incomes below its BRIC peers, however there exists opportunities and capabilities to fulfil its growth potential, thus it can become a source for driving the world economy and a key contributor in the recovery of world economy from the recent recession. India’s forthcoming urbanisation process has implications for increasing demand for housing, infrastructure, and demand for consumer durables. Given the considerable implications, India’s ability to turn potential into reality should be of importance not only for its 1.1bn population, but also for the recovery and growth of the global economy.
10. The People’s Republic of China is the world’s second largest economy both in nominal and PPP terms after the United States. It is the world’s fastest-growing economy, with average growth rates of 10% for the past 30 years. It is also the largest exporter and second largest importer of commodities in the world. The country’s per capita GDP (PPP) is $6,567 (98th in the IMF ranking) in 2009. The provinces in coastal area of China are more developed, as compared to the regions in the hinterland which are less developed.
11. According to the experts, China and India “are competing with the west for “intellectual capital” by seeking to build state of the art facilities, investing in high, value-added and technologically intensive sector, and utilising successfully technological knowhow to generate entrepreneurial activity. However India needs to resolve its problem of mass poverty and thus long-term political stability and achieving immense potential growth prospects. According to My Pocket World in Figures, 2007 Edition edited by The Economist, adult literacy in China is 90.9%, Brazil 88.6%, Russia 99,4% and India a mere 61%. What do foreign investors want to do in a country with 40% illiterate people? [6]
12. Russia has been a star performer in 2008 in the entire Euro-Asian region. This performance is not only driven by high-energy prices but also market driven. Instead of oil and gas – which will remain solid performers for Russia – the country economy will be driven by domestic consumption growth, higher demand for major commodities and enhanced political stability. Russia has great potential both as market and as resource. The biggest strength of Russia is its natural resource wealth which has attracted foreign investor’s attention. Off late Russia has consolidated its influence over Central Asia’s energy resources and has increased its strategic dominance in Europe’s energy markets [7] .
METHODOLOGY Statement of the Problem 13. There is an requirement for India to move beyond cosmetic ties and forge cooperation in various fields of trade, technology and defense sector to fuel her economic growth.
Hypothesis 14. India has the potential to maximize engagement with other countries in the BRIC forum in fulfilling her aspirations of developing into an major world economic power by 2030.
Justification for the Study 15. The significance of emerging Indian