Consequences of Inequality and How Should Policymakers Respond
Inter-regional inequalities and policies to tackle them have had an increase in popularity over the last decade and for good reason from 1999-2007 inequalities in regions within enlarged Europe at the NUTS3 level increased by 8%. In the same time period, national inequalities have decreased by 45% . This is generally in line with earlier works which suggest there is evidence that inter-regional income inequality will converge at a Gini index of 40%, so should this be a cause for concern for policy makers?
This essay will explore the causes of rising inter-regional inequalities generally alongside a case study of Germany. It will be done in the following structure: the first section will explore what inequality is and analyse the patterns in inter-regional inequality. The second section will investigate the causes of these patterns and the final part will look at the consequences of inequality and how policymakers should respond to the challenges.
Inequalities can fall into one of two categories, either they are income or non-income inequalities. Income inequalities, as the name implies associated with individual and/or household income. Non income inequalities can include things such as inequality of opportunities, education and access to public services. Typically, studies are much more focused on income inequalities and this essay will mainly focus on income inequalities but will briefly cover some aspects of non-income inequalities as well.
Before I review the trends in regional income it is important to discuss the methods used to measure income inequality. The most common three methods seen are Gini coefficient, top decile earnings relative to the total income and GDP per capita. In this paper, I will mostly use GDP per capita. These measurements are not completely comparable as two societies or regions could have the same GDP per capita but different opportunities for individuals.
We can see a clear trend showing lower GDP per capita in the regions that used to make up East Germany relative to the regions compared with the regions that used to be in West Germany. Since the 2000s, GDP per capita and income in the former East Germany Regions have been fixed at around 80% of those in the west. This east- west divide also shows significant wealth inequality with an adult living in the west having around 2.35x the amount of assets compared to their eastern counterparts. Although this example is specific to Germany the same trend of regional divides can be seen in many developed and emerging countries across the world.
In general, recent studies corroborate the fact that income inequality in urban areas is greater than that of rural areas. This is consistent with the data we can see in Figure 1. We can see that the difference, on average, between urban metropolitan areas is greater than in rural areas. The biggest difference in GDP per capita between two cities in Germany is just over 150,000 euros.
According to (Biewen and Juhasz, 2010) the three most prominent factors that cause rising income inequality are rising unemployment, rising inequality in market returns and changes in the tax system. These factors play such a large role that they can be attributed to 75% of the increase in income inequality in Germany.
This large increase in unemployment has mainly been caused by technological change and a change in industrial composition. Large technological changes have caused large shift in the industrial composition throughout the world. Large portions of primary sector workers have now become redundant due to automation and globalisation.
This shift is problematic, as it causes a difference in the skills that the workforce possesses, and the skills required for these technological jobs, meaning that workers cannot capitalise on these new jobs being created. In the short run, this generates an increase in inequality and causes a large shift in employment rates. This mainly causes metropolitan areas to boom due to the expansion of new industries, but it causes a decline in regions that were dependant on these declining and stagnant industries, widening regional income inequality.
Figure 2 shows the unemployment rate in Germany between 1994 and 2008. If we compare this with figure 3 which shows the Gini coefficient of Germany between the same time period. We can see that when employment is at its peak in 2005 that the Gini coefficient is also at its peak. This signifies a correlation between the two and corroborates with Biewen and Juhasz’s findings.
Both local and national government policy also has a strong impact on rising inter-regional inequalities in the forms of tax rates, strength of unions and minimum wage rules. A good example of this would be the trend of reduced income and wealth taxes in western developed since the 1990s. The reason this increased income inequality was that the reduction was greater for higher income workers relative to lower income workers. This less progressive form of taxation leads to an increase in wage distribution and allows high income earners to increasing benefit from capital gains.
There are also socio-demographic factors that have a role in rising inter-regional income inequalities. These include the age composition of the region and female participation in the labour market. From (Breau et al, 2020) we can see that there is a positive correlation between regional income inequality and female participation rates. An increasing elderly population due to skilled young workers moving away or otherwise also leads to an increase in inter-regional income inequalities.
Cultural norms play a crucial role in deciding the access to education and labour participation of minority groups. In Africa and South-east Asia there is a large disparity between the average education received by boys compared to girls. This is due to there being a societal norm that women are to be stay at home mothers and investing in their education would be wasteful.
In developing countries and potentially some developed countries we can also see that there is evidence to suggest that there is a direct correlation between inter-regional income and non-income inequality. An example of this can be seen in the access to healthcare for South Africans, in terms of distance, is two time higher in richer provinces such as Gauteng relative to poorer provinces such as Limpopo.
Regional income inequality has risen over the past 15 years (IMF) so the question arises whether governments should intervene and try to reduce inter-regional inequalities. This answer varies case to case but for an overwhelming majority of cases it is in their best interest for governments to intervene in inter-regional inequalities.
This is due to rising inter-regional inequality having a range of consequences with one of the main ones being a dampening of economic growth. In fact, from we can see that slight changes to income inequality can lead to significant changes in GDP per capita especially for low income earners. The 75th percentile of earners experience a -5.3% income per capita from a one percentage point rise in the Gini coefficient. This leads to a strong link between inequality and poverty as rising income inequality pushes a higher proportion of people into relative poverty.
An increase in inter-regional inequality can also lead to political and social consequences. A rise in inequality can normally be partially attributed to a rise in unemployment rate as seen in figures 2 and 3. Unemployment not only causes a loss in income it also has various social effects. Rising unemployment can lead to an increase in alienation causing the rise of nationalist political movements and there is evidence to show that being unemployed leads to a higher suicide rate in western societies. This can lead to a loss in human capital, rising crime rates and political instability.
This leads policy makers to ponder what kind of policy would be best to tackle this issue. Traditionally, a space-neutral policy has always been advocated with a report by the world bank in 2009 endorsing it but recently we have seen a shift in favour of place-based policies. Traditionally space-neutral policies focus on the development of human capital and establishment of new firms. These policies are strong advocates for agglomeration and believe that policies should be focused on growing regions rather than the lagging regions.
These policies were often failed in the short term as firms who moved there due to incentives such as corporate tax cuts or subsidies, left as soon as they stopped. 2009 was a real turning point in the design of policy as it a shift in favour of place-based policy. These policies focused on boosting the growth of these declining regions and maximising the development potential of these regions rather than on the growing regions, as was conventional at the time.
To conclude, despite seeing a trend of national inequality levels decreasing there has been an increase in the levels of regional inequalities. The main causes of rising inter-regional inequality are rising unemployment, rising inequality in market returns and changes in taxation. Socio-demographic factors also play a role in rising inter-regional inequalities. There is a mixture of economic, political and social consequences from this rising inequality. Policy makers should respond to this challenge by the implementation of place-based policies with a goal to maximise development potential of each region.
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