Impact of Recession on Inequality - Coursework Example

IMPACT OF RECESSION ON INEQUALITY Introduction Inequality is defined as lack of equality. It signifies categorisation of persons based on circumstances and the degree of certain privileges. Inequality may occur in wealth distribution, expenditures, consumption, or disposable income, and earnings. Interestingly, these differences have been there in the society. However, the great recession may have played a significant role in magnifying every form of inequality. The great recession impacted negatively on unemployment rates and dropping of house prices, which were sustained hence leading to adverse consequences. Many populations ended up with little wealth owing to dwindling asset prices. Therefore, the great recession played a significant role in the redistribution leading to fall in social welfare. The United Kingdom had a fare share of these challenges. The coalition government came up with policies during the period. However, whether those policies buffered the impacts of great recession on several aspects of inequality received wide literature coverage. Therefore, assessing the impact of great recession on inequality within the UK forms the main objective of the essay. The essay illustrated the evidence for inequality in the UK by assessing several elements of inequality. Besides, it examined the impact of great recession on economic inequality as well as redistribution in the UK and compare the findings with other OCED countries. The Effects of policy on inequality, poverty, and living standards The great recession is one historical event that constituted watershed for many businesses. Economic literatures reported that careless banking concepts played a significant role in its emergence as well as the entrenched social inequalities (Jin et al., 2014). Inequalities are associated with stagnant consumer income. The most affected level of incomes was the middle and the lower class. The IFS (2015, Living Standards) found that young people had suffered the most in terms of income over the course of 2007-08 to the present day. These were largely due to their reliance on the labour market for their income. However, these were in contrast to older people who saw their incomes rising over that same period. There were substantial changes in the cost of housing because of mortgage interest rates plummeting. The change improved the position of people who own their homes, the middle, and top of the income distribution leaving the lower cadre in jeopardy (Cribb et al., 2012; 2013). The coalition government took office after the Great Recession, just as household incomes were beginning their subsequent and inevitable decline (Cribb et al., 2012; 2013). During the recession, the income continued rising slowly. However, from 2009/10 when the household income was at the pair it attained the lowest value (4%) during the 2011/12. The main drivers were the unemployment and the workers pay. Although the unemployment index recovered sharply, the same trend was not reported in the worker’s pay (Hood and Levell, 2014a; b). Such findings demonstrated consistency for the lack of growth in productivity from 2011. The policies introduced brought about significant losses amounting to £489 per year. However, the mean gain reported for the year was £321 (Jenkins 2015). The benefits were attributed to the cutting of direct tax while during the same time a loss of £333 was reported (Hood and Levell, 2014a; b). The loss led to increasing indirect taxation. The most affected group during the period were the low-income households, especially the working age. The effort by the coalition government to cut benefits had a significant effect on their income tax and other benefits. The government attained that by lowering the percentage income of the low-income household groups (Browne and Elming, 2015). However, people in the middle-income category without children were the most beneficiary of the changes introduced by the coalition government. For instance, they gained from the policies of increased income taxation of personal allowances. Besides, they were not affected by efforts to cutting the benefits. These measures depicted that increasing personal allowances and reducing the benefits, especially for the non-working groups, it strengthened the financial incentives across all the household groups (Belfield et al 2015). (Jenkins 2015) Figure 1: income distribution The above diagram shows the highly skewed income distribution. It documents those households with income below the mean to constitute the two-thirds, whereas the long-tail, which forms about 2% of the households has income more than £1,100 (IFS, 2015). These findings reveals that if one is living alone and gets £1,500 as a net monthly income after taxation he or she will fall in the 83rd percentile. Contrary, if the same person earning the same amount but have two young children and a partner, the person will fall in the 34th percentile. However, if an individual earns a net income of £900 after taxation, such persons will fall in the 49th percentile. (Jenkins 2015) Figure 2: depicting trends of real income from 1961 to 2011 The grey stripes in figure 2 above shows demarcation of recessions. The figure illustrates income levels at 90th, 50th, and 10th percentiles and their mean value. All the percentiles are depicted to rise by the fifth year after 1961. However,, recessions impacts the trends because it slows down the progress. Notably, 2007 (recent recession) shows the sharpest deviation from the rising outlook. Another observation of litl growth was during 1990s while slow growth of income reported during the early 2000s. (Jenkins 2015) Figure 3: illustration of income inequality since 1961 The figure 3 above demonstrates the growth of gap between the bottom earners and those in the top scale as a form of inequality. However, figure 3 gives a summarised from of the inequality using ratio p90/p10 (90th -10th percentile) as well as the Gini coefficient. These illustrations show a substancial trend in the rise of inequality for the past 50 years (1961 to 2011). Interesting trend was the rise of p90/p10 by one half while the Gini by two-third. However, most changes in the inequality took place during the 1980s. The two decades before and afte that period were relatel flat, signifying the exceptional circumstances during the 1980s. During 1991, the p90/p10 ratio reported a distinct decline, which was not replicated in Gini coefficient, perhaps these trends are attributed to income distributions below the median that are not sensitive to Gini. (Jenkins 2015) Figure 4: comparing trends of inequality with 20 OECD nations The analysis were based on increasing, falling, or constant level of inequality between 1980 to 2012. The Gini coefficient was used to measure these levels. The OECD value was 0.32, while the UK measurement was 0.34 for 2011/12, which was slightly above the mean value for the ranked 21 countries. However, in case the data for turkey and Mexico were left out, the UK was demonstrated high levels of inequality relative to most rich nations. Despite these trends, the level of inequality in US was greater than the UK (Figure 4). Comparing UK with other countries Pre-recession under George w bush the government was very much focused on trickledown effect whereby they hoped that the rich getting richer would have the effect of their wealth increasing the living standards of the poorer income households. However since Obama has ascend to leadership, it has been clear that the focus has been on helping lower and middle-class families for example Obamacare. It brought about a strange reaction from the population however as many people have rejected the plan even though it is aimed to help them. In the last 30 years, US inequality has increased by 15% from 0.34 to 0.39. As mentioned earlier, the top income share has increased significantly from 8% to 20% between 1980 2010. The 90/10 ratio was 16 with only Mexico and Chile higher in the OECD in 2011/2012. Another example of this is the share of income growth. Over the last 40 years, income in the US has increased by an average of 1% per annum however if you take out the top 1% of earners then this drops to only 0.6%. The years 2000 to 2008 showed that the poorest groups experienced the largest decline of the average income by 10%. However, during the recession (2008) and 2010, the value fell by 7% and then recovered to a modest range from 2011/12 (OECD: 2014). From 2000 onward, it has declined, leaving the US bottom 10 percent only the 18th highest earners in OECD. Concerning the recession, a lot of the inequality arose from loss of employment; this could be because the first people to be made redundant in a company will not be the bosses but the lower income workers. Therefore, the unemployment for lower income workers fell significantly compared to higher income earners. There was also a significant shift in the labour market as more people moved into part-time work and as a result took a decrease in their income especially in the lower income households. Top income shares did fall quickly in the recession but recovered much more quickly than lower income earners (Hood and Levell, 2014a). The pre-tax income inequality in the US from 2000- mid 2000's is actually equal to Spain and Scandinavian countries at 0.57 however with the tax system and welfare state of the US. After-tax income inequality does not take as much of a decline in these countries only falling to 0.42 leaving it the highest after-tax income inequality in the OECD (economist: 2013). The shares of the top one percent income doubled from 4% to 8% from 1980 to 2010. However, a rapid fall of income inequality was reported when recession began. For instance in 2012/13, the 90/10 ratio became 3.9, which was the lowest value ever reported since 1980s. One likely driving factor behind the steady income growth amongst those with lower incomes between 2007–08 and 2009–10 was higher income from benefits and tax credits. As mentioned in Section 2.3, average income received from this source grew by 5.6% per year in real terms during these two years. Income growth for the top 1% has fallen since the recession due to the poor performance of the FTSE, as a large proportion of their income comes from the financial markets. In particular, the substantial recovery in top incomes in 2009–10 coincides with the sharp recovery in the stock market, with incomes at the top percentile as measured in HBAI growing by 13%, while the FTSE 100 index increased by more than 30% (Cribb et al., 2013). The Atkinson measure allows one to choose a value for society’s aversion to inequality, defining the amount that society considers it necessary to give to a ‘poor’ person, having taken a given amount of income from a ‘rich’ person, in order to keep overall social welfare the same. The value we have chosen for this parameter reflects a society that considers it necessary to give £33 to a ‘poor’ person, having taken £100 from a ‘rich’ person, in order to keep overall social welfare the same (this is a relatively inequality-averse society). This measure was discussed in more detail in Appendix C of Brewer, Goodman, Shaw, and Sibieta (2006). The future of UK income inequality is unknown, higher rates of tax for high earners are set to reduce earnings for high earners. However, cuts to the benefits system is set to reduce low-income households. Inequality will hang on employment and how well that recovers, along with average wages (Cribb and Joyce, 2015). There has been higher inflation in food and fuel bills, and low inflation for mortgage payments, as a result. Refer to the two graphs. Without inflation taken into account, low incomes were better off, however now their incomes fall instead of rise. Middle incomes better off. After adjusting for average inflation, median income among households with children is estimated to be 0.4% higher in 2014–15 than in 2007–08, while median income among households without children is 3.8% lower than prior to the recession (Belfield et al. 2014). After taking into account differential inflation, the median income for adults (>60years) was higher by 1% during the 2014/15 period than the 2007/08. The median income of those aged 31–59 is projected to be 2.5% below its pre-crisis level in 2014–15, despite having risen by 1.2% in the last two years as the labour market has started to recover. Meanwhile, young adults aged 22–30 have seen the largest falls in their income since the recession, with their income projected to be 7.6% lower in 2014–15 than in 2007–08 (IFS, 2015). The Concepts of Poverty as Inequality Natural rights libertarians like Nozick (1974) regard taxation as theft as it takes money from people that they would have used it in a different way, and he also considers taxation as a form of slavery, since people are effectively forced to spend part of their time working for the government. However, the Empirical libertarians such as Hayek and Friedman take extremely lower view than Nozick. They believe that the state has no distributional role, except in the case of particular public goods and measures to alleviate extreme poverty. The view places great importance on the individual and argues for smaller governments. It re-emerged as a prominent theory in the 1970’s and 1980’s and the US Tea Party around 2010 is another good example. In summary, libertarians will not be as about worried about inequality and poverty as liberals or collectivists. Utilitarian’s aim to maximize total welfare and are therefore not concerned about an individual’s welfare, only the sum of all the individuals’ welfare in society. Therefore, if a tax policy that favours high earners boosts the rich’s utility by more than poor people’s utility falls then it is deemed a good policy by the utilitarian. However, the Rawls talks about the veil of ignorance and how using that concept, the rational choice for society is to select principle according to the ‘maximin rule’, which means that policies aimed at capitalizing on the situations of the individuals below the ladder. The collectivists agree on the importance of equality. The experiment with communism in Stalinist Russia provides a clear example of what happens when equality destroys incentives. Lack of reward to the efforts of the workers meant that they lacked the incentives that could have rejuvenated them to work hard. Galor and Zeira (1993) consider the impact of inequality on investment in physical and human capital in a world of borrowing constraints. For example, if there are borrowing constraints in the context of access to higher education, then poor people’s ability to increase their human capital is severely diminished. They cannot afford to invest in education, as they have not had the chance to accumulate savings. In contrast, richer families can afford to pay for their children’s education. Such trends deny talented people from poor backgrounds the opportunity to increase their human capital and the whole economy suffers as a result. Productivity is lower and this creates a negative relationship between inequality and growth. This effect plays out over a long period with the economy converging to a long-run equilibrium. This grinds social mobility to a halt; as those who can initially afford to take part in higher education go on to earn more money, leaving bequests to their children, enabling them to enjoy higher education, continuing the cycle. Poor people who may have more productive than the rich have, generate fewer earnings, preventing them saving and their children will face the same dilemma they did. Galor and Zeira provide the fundamental analysis and the other papers extend it, focusing on different variations of the original idea. Deininger and Squire (1998) find that inequality is very damaging to investment in human capital, but an insignificant effect on physical capital investment. Consequently, it is through schooling that inequality has its strongest effect on growth. Neves and Silva (2010) state that land inequality and human capital inequality exert a greater impact on growth compared to income inequality. They discuss two reasons why this is the case. Firstly, that there are several problems associated with income distribution data. However, there is no particularly strong evidence to suggest that these problems are behind the less significant relationship between income inequality and growth. Secondly, that as proposed by Deininger and Squire (1998), that it is, in fact, the wealth inequality distribution that explains the relationship between inequality and growth as opposed to the income distribution. Land and human capital inequality can be seen as proxies for wealth inequality. Neves and Silva (2010) say that the there is empirical evidence to support the imperfect credit market channel but results are far from conclusive. Neves and Silva (2010) outline how the distribution of income influences growth due to the effect of public expenditure and taxation. The models say that public goods are funded by a proportional tax on capital, but it is taken to mean any policy that redistributes income to unskilled labour and reduces the incentive to accumulate capital. Tax revenues are redistributed through a lump sum to all individuals, and since they all have a different endowment of labour and capital, they will all have differing views on what the typical tax rate should be. Individuals with a lower share of capital will prefer a higher tax rate. Since fiscal policy is decided by majority voting, one can use the median voter theorem to investigate the relationship between inequality and growth: when there is equitable distribution of economic resources, the mean voters’ gets endowed with the capital, and consequently, the lower the equilibrium level of taxation. Thus, taxation and redistributive government expenditure increase as inequality increases. This mechanism, which Perotti (1996) calls a “political mechanism,” constitutes the first link of this approach. The second link – the “economic mechanism” – is based on the idea that taxation and redistribution, in turn, are harmful to growth because of their distortionary effects on savings and investment. Combining these two links, we should expect a negative effect of inequality on growth.” (Neves and Silva, 2010, p. 6-7). There is, however, no empirical evidence supporting the fiscal policy channel. Inequality can also have an adverse effect on growth because of the socio-political instability it can cause. Alesina and Perotti (1996) argue that high levels of inequality leads to greater social-political instability, because it increases the likelihood of rent-seeking behaviour, protests, revolutions, and coups. Higher levels of socio-political instability have a negative effect on investment, because it creates uncertainty for businesses can disrupt production and the productivity of labour and capital fall as a result. These effects harm economic growth. Kaldor (1956) argues that richer people have a higher marginal propensity to save than the poor people do. Therefore, increasing inequality channels income towards people who save more, aggregate savings increases, leading to greater investment and growth. There are, however, no theoretical models addressing this channel. Barro (2000) found no correlation between income inequality and investment ratios. Therefore, found no evidence suggesting the aggregate saving rate, a rate that typically influences the investment ratio, is affected by the amount of income inequality. Measurement of poverty and inequality and policy implication According to Foster et al., (2013), measurement of inequality and poverty requires a depth understanding of the relationship between the social variables, economic factors and the poverty. These strategies help by providing a comprehensive strategy for measuring poverty. There are three processes for measuring poverty. These involve selection of space for assessing poverty. These spaces may include monetary units, consumption, or income (Foster et al., 2013). The second stage involve identification of the poor by selection of the poverty line to signify the lowest level of the accepted consumption or income. The last stage is the aggregation of data into poverty measurement. The aggregation uses a headcount ratio by calculating the share of poor populations. The most appropriate way of evaluating inequality involves using smoothing income to assess inequality between group. This involves assessing inequality of incomes within subgroups and comparing that with the mean of the subgroup before applying measures of inequality to the smoothed distribution (Foster et al., 2013). The method is also appropriate for measuring a country’s inequality in opportunities. The process commences by the identification of circumstances that a person is not able to control; these circumstances are linked to income levels (lower and higher levels). The method makes it possible to divide population into groups of individuals that share similar circumstances to allow smoothening of the distribution hence suppress the inequalities in the groups. These are used for measuring the inequalities across the sub groupings. Policy makers using the distribution of the poor people across urban and rural settings should consider some factors before applying the headcount ratios (Foster et al., 2013). The headcount ration misses the important facts like capturing the residential information of most poor people. For instance, is a location has lower headcount ratio, yet the place may have high population it may signify that the poor people are many. Therefore, policy makers should focus on places that have high ratios and a larger share of the poor population. References Alesina, A. and Perotti, R.  (1996) Income Distribution, Political Instability and Investment, European Economic Review, 40:1203-1228.   Barro, R. (2000) Inequality and Growth in a Panel of Countries, Journal of Economic Growth, 5: 5-32.   Belfield, C. Cribb, J.  Hood A. and Joyce R. (2014) Living Standards, Poverty and Inequality in the UK: 2014, IFS Report R96, 2014.  Belfield, D., Chandler, C. and Joyce, R. (2015) Housing: trends in prices, costs and tenure, IFS Briefing Note BN161, 2015.  Browne J. and Elming W.  (2015) The effect of the coalition’s tax and benefit changes on household incomes and work incentives, IFS Briefing Note BN159, 2015.  Cribb, J.  Hood, A. Joyce R. and Phillips D. (2013) Living Standards, Poverty and Inequality in the UK: 2013, IFS Report R81, 2013.  Cribb, J.  Joyce R. and Phillips D. (2012) Living Standards, Poverty and Inequality in the UK: 2012, IFS Commentary C124, 2012.  Cribb, J. and R. Joyce. (2015) Earnings since the recession, in C. Emmerson, P. Johnson and R. Joyce (eds), The IFS Green Budget: retrieved from  http://www.ifs.org.uk/uploads/gb/gb2015/ch2_gb2015.pdf.   Deininger, K. and L. Squire (1998) New Ways of Looking at old Issues: Inequality and Growth, Journal of Development Economics, 57: 259-287.   Foster, J., Seth, S., Lokshin, M. And Sajaia, Z. (2013) A unified approach to measuring poverty and inequality, theory and practice. Washington DC: The World Bank Galor, O and Zeira, J. (1993) income distribution and macroeconomics, Review of Economic studies, 60: 35-52 Hood A.A. and Levell P.  (2014a) Measuring Poverty when Inflation Varies across Households, Joseph Rowntree Foundation Report, retrieved from http://www.jrf.org.uk/sites/files/jrf/poverty-inflation-households-full.pdf.  Hood, A.A. and Levell P. (2014b) The squeeze on incomes, in C. Emmerson, P. Johnson and H. Miller (eds), The IFS Green Budget: retrieved from,  http://www.ifs.org.uk/budgets/gb2014/gb2014_ch6.pdf.  IFS, (2015), Living Standards: Recent Trends and Future Challenges, retrieved from http://www.ifs.org.uk/wheredoyoufitin/   Jenkins, S.P. (2015) The income distribution in the UK: A picture of advantage and disadvantage;London School of Economics, IZA, and Institute for Social and Economic Research, University of Essex Jin, W.  Joyce, R. Phillips D. and Sibieta L.  (2011) Poverty and Inequality in the UK: 2011,  IFS Commentary C118, 2011.  Kaldor, N. (1956) Alternative Theories of Distribution, Review of Economic Studies, 23(2): 83-100.  Neves, P. C. and Silva S. T. (2010) Inequality and Growth: Uncovering the Main Conclusions from the Empirics, Working Papers (FEP) – Universidad do Porto, 281: 1-35.  Perotti, R. (1996) Growth, Income Distribution, and Democracy: What the Data Say, Journal of Economic Growth 1:149-187.   Read More