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User:NP824/Spatial inequality

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Spatial inequality refers to the unequal distribution of income and resources across geographical regions.[1] Attributable to regional differences in infrastructure, geographical features (presence of mountains, coastlines, particular climates, etc.) and economies of agglomeration,[2] such inequality remains central to public policy discussions regarding economic inequality.[1]

Whilst urban areas tend to have higher nominal wages than rural areas, the cost-of-living and availability of skilled work correlates to regional divergences in real income and output. [2] Additionally, the spatial component of public infrastructure affects access to quality healthcare and education (key elements of human capital and worker productivity). [3]

Determinants

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Urbanization and Economies of Agglomeration

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The relationship between population density and productivity is considered to play a key role in the divergence between cities and rural areas with respect to economic capital, cultural capital, and social capital. [4] In particular, the clustering of agriculture activities versus manufacturing endeavors informs much of the urban-rural wage gap, with different communities undergoing urbanization at differing rates. [5] In terms of organization and the set-up of linkages throughout the supply chain, the core-periphery model suggests that manufacturing tends to form the "core" of an industrial cluster, with agricultural activity tending to take place on the "periphery" of such urban formations. [6] Such patterns permit greater economies of scale to be realized. [6]

Agglomeration economies refer to the benefits gained from industrial clustering and city-formation.[7] With the observed savings in transportation costs from this phenomenon being central to the study of economic geography [7][6], the positive externalities afforded by such urbanization (and the mechanisms by which they occur) remain to be of interest. [7]

Population concentration and the clustering of particular industries allows for the pooling of workers, thus giving way to greater matching between the business needs of firms and workers' specific skillsets. [6] Such specialization also allows for knowledge spillovers and greater exchange of ideas, thus fostering a comparative advantage that can be especially advantageous for realizing gains from trade and having higher productivity. [6]

Natural Resources and Geographical Features

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Natural resource availability affects industry prevalence, as well as the clustering of natural-resource dependent economic activities to suitable geographical regions and climates. [1] Whilst the resource curse theory suggests that an over-reliance of employment and economic activity on the abundance of natural resources (including forestry, fossil fuels, mineral deposits, etc.) can lead to price volatility and instability, the exogenously determined geographical features of the area determine its ability to produce traditional agricultural goods and exports, thus informing the composition of employment in the region. [5]

Regional Infrastructure

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Regions with access to strong transportation networks (including highways, railways, airports etc.) are more likely to benefit from external trade in comparison to remote regions. [5] As transportation costs and logistics inform much of the clustering of economic activity within a region [7], the geographical concentration of particular industries informs the extent to which particular physical infrastructures must be developed and invested in to support the needs of specific localities. [3]

Social infrastructural components, which impact health and education standards (hospitals, schools, public libraries, etc.) additionally influence quality-of-life conditions and the well-being of workers, and thus their choices with respect to selection regions/ communities to live in. [3] As such, city planning and the provision of public infrastructure and services remains essential to public policy considerations for rapidly urbanizing communities. [8]

For instance, the spatial patterns of environmental factors and hospital accessibility may impact public health outcomes, such as COVID-19 mortality rates within a nation. [9]

Furthermore, as families of similar incomes tend to cluster, further segregation of socio-economic classes is propagated by schooling environments. [10] This adversely effects the opportunities available to children from low-income backgrounds, and reduces the ability for social-mobility needed to escape the poverty trap and generational poverty. [10][11]

Investment Choices, Trade, and Migration

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As different communities may not have similar comparative advantage due to variations in natural resource composition and abundance, foreign trade and globalization are thought to play a key role in influencing spatial inequality as well. [5] In particular, economies undergoing rapid trade liberalization have been observed to actually have increases in poverty rates and income inequality, in-spite of nation-wide benefits of economic growth being realized, as urban-rural gaps tend to widen. [1] Additionally, migration patterns from rural to urban areas in developing nations are observed to be a labor market adjustment to an increasing shift in importance from agriculture to manufacturing. [12]

Measurement

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Output and Productivity

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The distribution of income within a nation can first be nominally estimated from local datasets, and then subsequently adjusted to account for regional differences in price-levels. [13] Such a procedure allows for comparisons to be made in real-terms and across different localities [13], which is especially pertinent when national-level inequalities are mostly influenced by regional disparities in income and cost of living. [14] However, the level of disaggregation (granularity of geo-spatial units considered) and the number of localities selected for comparison varies across academic studies. [14] For instance, geographic sub-groups can be considered at the state level, as an urban/rural divide, or even within-component (differences between households belonging to the same group or community). [15] Typical econometric studies will then design and use regression models to analyze the effects of density, industry location, or related variables on regional differences in output or costs. [13][14][3]

While nominal wages tend to higher in cities and urban regions, the same is not necessarily true of real wages, as rising housing costs and expenses tend to offset these benefits. [2]

Empirical Challenges

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The availability and reliability of local data remains a barrier to accurate estimation in academic studies. [13][14] The typical limitations of econometric studies may also impact the soundness of empirical results and conclusions. As such, there remains no unified theory within economic geography to provide a broadly-accepted causal explanation for spatial inequality. [5]

In particular, an inherent difficulty to comparing urban and rural regions is the vast disparity in quality and variety of goods and services enjoyed by the typical household in either type of community. [2] Furthermore, differences in disposable income and composition of spending pose further challenges to comparative approaches. [10]

Whist the Gini coefficient and Theil index remain as popular income inequality metrics, these summary statistics do not allow for the decomposition of inequality into multiple dimensions, and thus are insufficient for the multi-faceted analysis required to study spatially-dependent inequalities. [3]

See Also

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  • Economic Inequality – Distribution of income or wealth between different groups
  • economies of agglomeration – Urban development in locations generating cost savings
  • Gains from trade – net benefits to agents
  • Redlining – Systemic denial of services to some areas
  • Returns to scale – Microeconomic concept
  • Urban economics – Economic study of urban areas
  • Urbanization – Process of population movement to cities
  • Rural Development – Improving quality of life in rural areas

Further Reading

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References

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  1. ^ a b c d Ravi, K. S. M., & Venables, A. (2005). Spatial Inequality and Development. In Spatial inequality and development (pp. 3–12). essay, Oxford University Press.
  2. ^ a b c d Romero, Jessie and Schwartzman, Felipe F. Inequality in and across Cities. October 2018, No. 18-10. Federal Reserve Bank of Richmond Economic Brief.
  3. ^ a b c d e Lall, & Chakravorty, S. (2005). Industrial Location and Spatial Inequality: Theory and Evidence from India. Review of Development Economics, 9(1), 47–68. https://doi.org/10.1111/j.1467-9361.2005.00263.x
  4. ^ Israel, & Frenkel, A. (2018). Social justice and spatial inequality: Toward a conceptual framework. Progress in Human Geography, 42(5), 647–665. https://doi.org/10.1177/0309132517702969\
  5. ^ a b c d e Kim, Sukkoo. 2008. Spatial Inequality and Economic Development : Theories, Facts, and Policies. Commission on Growth and Development Working Paper;No. 16. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/28050 License: CC BY 3.0 IGO.
  6. ^ a b c d e Krugman, P. (1991). Increasing Returns and Economic Geography. In The Journal of Political Economy, Vol. 99, No. 3, pp. 483–499.
  7. ^ a b c d Glaeser, Edward L. (February 2010). "Agglomeration Economics". National Bureau of Economic Research (NBER). University of Chicago Press: 1–14. ISBN 0-226-29789-6.
  8. ^ Ahimah-Agyakwah, Nketiah-Amponsah, E., & Agyire-Tettey, F. (2022). Urbanization and poverty in Sub-Saharan Africa: evidence from dynamic panel data analysis of selected urbanizing countries. Cogent Economics & Finance, 10(1). https://doi.org/10.1080/23322039.2022.2109282
  9. ^ Sun, Hu, X., & Xie, J. (2021). Spatial inequalities of COVID-19 mortality rate in relation to socioeconomic and environmental factors across England. The Science of the Total Environment, 758, 143595–. https://doi.org/10.1016/j.scitotenv.2020.143595
  10. ^ a b c Boulant, Brezzi, M., & Veneri, P. (2016). Income Levels And Inequality in Metropolitan Areas A Comparative Approach in OECD Countries / Justine Boulant, Monica Brezzi and Paolo Veneri. In Income Levels And Inequality in Metropolitan Areas A Comparative Approach in OECD Countries. OECD Publishing.
  11. ^ Banerjee, Abhijit V., and Esther Duflo. Poor Economics: Rethinking Poverty and the Ways to End It. India: Random House India, 2013.
  12. ^ “Lall, Somik V.; Selod, Harris; Shalizi, Zmarak. 2006. Rural-Urban Migration in Developing Countries : A Survey of Theoretical Predictions and Empirical Findings. Policy Research Working Paper; No. 3915. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/8669 License: CC BY 3.0 IGO.”
  13. ^ a b c d Aten, B., & Heston, A. (2005). Spatial Inequality and Development. In Spatial inequality and development (pp. 15–36). essay, Oxford University Press.
  14. ^ a b c d Elbers, C., et al. (2005). Spatial Inequality and Development. In Spatial inequality and development (pp. 37–60). essay, Oxford University Press.
  15. ^ Spatial inequalities: across states or between rural and urban areas? (2017). In OECD Economic Surveys: India 2017 (pp. 141–142). OECD Publishing. https://doi.org/10.1787/eco_surveys-ind-2017-8-en
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