Impact of Economic Growth on Income Inequality: A Regional Perspective

Impact of Economic Growth on Income Inequality: A Regional Perspective Shibalee Majumdar and Mark Partridge Egalitarianism refers to the doctrine of the equality of mankind and the desirability of political, economic and social equality. In this paper, we are going to refer to the concept of economic equality. Theory shows that income inequality is a condition that prevails along with economic growth. According to the utilitarian view, income inequality must exist along with economic growth in order to maximize social welfare. This is in sharp contrast to the egalitarian view according to which, all members of the society should have equal access to all economic resources in terms of economic power, wealth and contribution. Kuznets (1955) introduced the inverted U-shaped Kuznets curve that showed that in an economic system, at the initial level of low economic growth, income inequality is low and as growth occurs, income inequality increases till a threshold, after which, income inequality decreases with increased economic growth. In the United States, income inequality remained stable till the 1970s but then began to increase as earnings increased. This has been called the great U-turn by Harris, et. al (1986). Partridge et. al (1996) notes that while Kuznets held the manufacturing sector as the main driver of the economic growth, the current economic growth is being spearheaded by the services sector. While one school of research shows how income inequality might harm economic growth, empirical studies show that in the United States, a positive linkage between economic growth and income inequality has existed since the 1970s. The causality between economic growth and income inequality is an important one. The relationship may differ depending on regions or size of an economy. Fallah and Partridge (2007) show that the impact of inequality on economic growth is opposite in rural and urban settings. Most of the research dealing with the inequality-growth relationship has either looked at the impact of inequality on economic growth (Fallah and Partridge, 2007) or the impact of various socio-economic variables on inequality. Though there has been some research on finding out the causality between economic growth and wage inequality, research assessing whether economic growth affects income inequality, and that too whether the degree of the impact varies between rural and urban regions, are few. The aim of this paper is to see how economic growth affects income inequality. Does improved economic growth lead to a more redistributive system of social welfare or does the polarization become more acute? Does the impact of economic growth on income inequality differ between metropolitan and non-metropolitan areas? Does inequality vary depending on the nature of the agglomeration or the demographic composition of a region? The empirical equation is: ginicsy = gcsy-1 + educsy + popcsy + lcsy + ethcsy + immigcsy + strcsy + σcs + σy + ε where, gini denotes the gini coefficient, g denotes per capita income, edu denotes educational attainment, pop denotes population density, l denotes labour market size, eth denotes ethnic diversity, immig denotes international immigration, str denotes the structural change index, σcs denotes state fixed effects and σy denotes time fixed effects. The subscripts c, s and y denotes county, state and year, respectively. A lagged value of the per capita income is used in order to avoid any endogeneity issues. The analysis for this paper will be done at the county-level. For the dependant variable and all explanatory variables except the per capita income, a panel will be constructed using county-level data for two decades, 1990 and 2000. The gini coefficient will be calculated using the income data from the U.S. Census Bureau. Data on per capita income, educational attainment, population density and international migration can be obtained from the U.S. Census Bureau. The ethnic diversity measure will be calculated using the population data from the U.S. Census Bureau. The structural change index will be calculated by using data from the Bureau of Economic Analysis, Regional Economic Information System. The aim of the paper is to find out whether per capita income (representing economic growth) has an impact on the gini coefficient (representing income inequality), and to show whether this impact varies between rural and urban areas. The expected results are as follows. Economic growth may have a negative impact on income inequality since economic growth is often positively associated with higher investments, higher employment-generating processes and higher employment, hence giving greater access to jobs and income to a larger number of people. The degree of the impact may vary between rural and urban areas because of the following reasons. A higher population density in the urban area may lead to greater job competition and hence lead to lower access to jobs than in rural areas. International immigration is usually higher in urban areas than in rural areas. The greater influx of immigrants, as well as often seen, the willingness of the immigrants to work at lower wages may lead to lower access to jobs for the locals. This should hold true for the low-skilled jobs. For the high-skilled jobs on the other hand, educational attainment of the people will play a more important role on their ability to get jobs in the urban areas than in the rural areas. However, growth may reduce income inequality in the urban areas because higher population density results in more personal contacts, better networking and access to information, and hence more opportunities to access more and better jobs. If the results show that economic growth has a negative impact on income inequality, it will be possible to comment on the causality of the inequality-growth relationship. More so, if it is seen that economic growth has a stronger impact in decreasing income inequality in the urban areas than in the rural areas, it will show that the higher wages and more diverse job opportunities in the urban areas have a greater spillover effect than in the rural areas. The policy implication such a result may have is that higher investments will have to be made in educational and vocational training in order to generate a stream of skilled labourers, which in turn will add to economic growth and thus will lead to lower income inequality and better social cohesion.Regional development, income inequality, spatial relation, Community/Rural/Urban Development,

Rural-Urban Migration and the Intergenerational Transmission of Wealth

Replaced with revised version of paper 07/24/08.Overlapping Generations Model, Rural-Urban Migration, Poverty Traps, Agglomeration Economies, Place-based Policies, Person-based Policies, Consumer/Household Economics, Labor and Human Capital, R13, R58, O15,

Interstitial crime analysis

Crime on public transport can be very difficult to analyse. 'Stealth crimes' like pick-pocketing present a particular challenge because victims often have an imprecise knowledge of the location and time of the offence. In this scenario crime has typically been recorded as happening at the reporting station (often at the ‘end of line’) which skews any analysis of the collective crime locations. Interstitial crime analysis (ICA) is a technique which overcomes this problem and improves the estimation of the spatial distribution of crime on networks when the exact location of offences is unknown. Based on the aoristic analysis technique (devised to estimate the temporal distribution of crime when only a time period is known), ICA is used to estimate the location of crimes in the interstices – the intervening spaces - of a network when the location is unknown

PERSISTENT POCKETS OF EXTREME AMERICAN POVERTY: PEOPLE OR PLACE BASED?

Over the past four decades almost 400 U.S. counties have persistently had poverty rates in excess of 20 percent. These counties are generally characterized by weak economies and disadvantaged populations. This raises the hotly debated question of whether poverty-reducing policies should be directed more at helping people or helping the places where they reside. Using a variety of regression approaches, including geographically weighted regression analysis, we consistently find that local job growth especially reduces poverty in persistent-poverty counties. We also find that persistent-poverty counties do not respond more sluggishly to exogenous shocks, nor do they experience more adverse spillover effects from their neighboring counties. Finally, we identify some key geographic differences in the poverty determining mechanism among persistent-poverty clusters. Taken together, these results indicate that place-based economic development has a potential role for reducing poverty in these counties.poverty, persistent poverty, economic development policies, place-based policies, Food Security and Poverty,

The Winner's Choice: Sustainable Economic Strategies for Successful 21st Century Regions

Throughout the second half of the 20th Century, urbanization, new technologies, rapid labor-saving productivity growth in primary industries, and improved highways combined to create large-scale rural-urban functionally integrated regions. These forces have raised the stakes for regions in their pursuit of economic development and growth, making successful regional policy even more important. Changes to the governance structures consistent with the increased interdependence within broad rural-urban regions will improve the region's competitiveness; adopting fad-based approaches and policies aimed at “picking winners” will be less fruitful. Going forward, continuing globalization and environmental sustainability have the potential to fundamentally reshape relative regional attractiveness.Regional Policy, Rural Development

Empirical Studies Applied to Software Process Models

Working Group Report: ICSE'99 Workshop on Empirical Studies of Software Development and Evolutio

The Geography of Rural American Poverty

Testimony of Mark Partridge, Ph.D. Swank Chair in Rural-Urban Policy, The Ohio State University. Before the House Ways and Means Committee, Subcommittee on Human Resources: The Geography of Rural American PovertyMuch of rural America is struggling today due to a downturn in the commodity super cycle that has hampered mining, energy, and agriculture. This is exacerbated by the fierce foreign competition that has faced lower-wage rural manufacturers for the last 20 years

Employment Growth and Income Inequality: Accounting for Spatial and Sectoral Differences

This paper revisits the inequality-growth relationship accounting for sectoral differences and focusing on US counties. For 8 two-digit industries of the NAICS classification, we estimated a conditional growth model where employment growth depends on regional income inequality and a number of control variables. Spatial econometrics techniques are used to account for spatial dependence. Results indicate that there is no association between employment growth and family income inequality for the Agriculture, Forestry, Fishing and Hunting sector and the Real Estate, Rental and Leasing sector. However, income inequality consistently shows a negative impact on employment growth in the construction sector, and results are mixed for other sectors such as: Manufacturing; Retail Trade; Professional Scientific and Technical Services; Accommodation and Food Services; Educational Services. In several sectors, mixed results were obtained when differentiation is made between urban and rural samples.employment growth, inequality, spatial dependence, Community/Rural/Urban Development, R0, R11, O15, D30,

Reevaluation of the Impact of Coal Mining on the Virginia State Budge

Downstream Strategies, an environmental consulting and policy analysis firm, published The Impact of Coal on the Virginia State Budget in 2012, finding that the coal mining industry was responsible for a net cost of 21.9 million USD to the Commonwealth in 2009 (considering only the Virginia General Assembly's General Fund and Transportation Fund revenues and expenditures). We provide a reanalysis of the same topic, considering the effect the presence of the coal industry has on the entire state budget that is not limited to the General Fund. We estimate that in our study year of 2011, the coal industry contributed 31.95 million USD in taxes and fees to the state while the Commonwealth's expenditures relating to the coal industry totaled 24.4 million USD. However, firms producing coal in Virginia also benefit from two exclusive refundable tax credits which we estimate combine to 49.37 million USD. We find that the coal industry was associated with a net cost of 36.7 million USD to the Virginia state budget in 2011