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On the dynamics of poverty and income inequality in US states

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Listed author(s):
  • Nicholas Apergis

Abstract

Purpose - This study seeks to provide answers to the following questions: Is there a relationship between poverty and income inequality in the short run/long run? Is the relationship unidirectional from income inequality to poverty as the previous studies assume, or is it bidirectional? Design/methodology/approach - The paper investigates the causality between income inequality and poverty within a multivariate framework using a panel data set of 50 US states over the period 1980 to 2004. Findings - The results reveal that a bidirectional relationship exists between poverty and income inequality both in the short run and in the long run. With respect to the short-run dynamics associated with poverty, both income inequality and the unemployment rate have a positive and statistically significant impact on poverty, a negative and statistically significant impact for real per capita personal income and level of education, while corruption is insignificant. In terms of the short-run dynamics associated with income inequality, poverty, the unemployment rate, real per capita personal income, and the level of education have a positive and statistically significant impact, while corruption has a statistically insignificant impact on income inequality. With regard to the long-run dynamics, the statistically significant error correction terms indicate the presence of a feedback relationship between poverty and income inequality. Originality/value - This study contributes to the existing empirical literature on several fronts. First, while previous studies rely on cross-country data, both the cross-sectional and time series variation of a panel data set of all 50 US states spanning the period 1980 to 2004 is exploited. Second, while the previous studies implicitly assume unidirectional causality from income inequality and poverty in their model specifications, the short-run and long-run causal dynamics between poverty and income inequality within a panel vector error correction model are explicitly examined.

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Article provided by Emerald Group Publishing in its journal Journal of Economic Studies.

Volume (Year): 38 (2011)
Issue (Month): 2 (May)
Pages: 132-143

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Handle: RePEc:eme:jespps:v:38:y:2011:i:2:p:132-143
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Keywords: Poverty; Income; Equal opportunities; United States of America;

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  1. Dollar, David & Kraay, Aart, 2002. "Growth Is Good for the Poor," Journal of Economic Growth, Springer, vol. 7(3), pages 195-225, September.
  2. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(03), pages 597-625, June.
  3. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
  4. Fisman, Raymond & Gatti, Roberta, 2002. "Decentralization and Corruption: Evidence from U.S. Federal Transfer Programs," Public Choice, Springer, vol. 113(1-2), pages 25-35, October.
  5. Dincer, Oguzhan C., 2008. "Ethnic and religious diversity and corruption," Economics Letters, Elsevier, vol. 99(1), pages 98-102, April.
  6. Glaeser, Edward L. & Saks, Raven E., 2006. "Corruption in America," Journal of Public Economics, Elsevier, vol. 90(6-7), pages 1053-1072, August.
  7. Peter Pedroni, 2000. "Fully Modified OLS for Heterogeneous Cointegrated Panels," Department of Economics Working Papers 2000-03, Department of Economics, Williams College.
  8. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
  9. Kalwij, Adriaan & Verschoor, Arjan, 2007. "Not by growth alone: The role of the distribution of income in regional diversity in poverty reduction," European Economic Review, Elsevier, vol. 51(4), pages 805-829, May.
  10. Pedroni, Peter, 1999. " Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 653-670, Special I.
  11. Fredriksson, Per G. & List, John A. & Millimet, Daniel L., 2003. "Bureaucratic corruption, environmental policy and inbound US FDI: theory and evidence," Journal of Public Economics, Elsevier, vol. 87(7-8), pages 1407-1430, August.
  12. Nicholas Apergis & Oguzhan Dincer & James Payne, 2010. "The relationship between corruption and income inequality in U.S. states: evidence from a panel cointegration and error correction model," Public Choice, Springer, vol. 145(1), pages 125-135, October.
  13. Timothy Besley & Robin Burgess, 2003. "Halving Global Poverty," Journal of Economic Perspectives, American Economic Association, vol. 17(3), pages 3-22, Summer.
  14. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
  15. Douglas Holtz-Eakin, 1986. "Testing for Individual Effects in Dynamic Models Using Panel Data," NBER Technical Working Papers 0057, National Bureau of Economic Research, Inc.
  16. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
  17. Rajeev Goel & Daniel Rich, 1989. "On the economic incentives for taking bribes," Public Choice, Springer, vol. 61(3), pages 269-275, June.
  18. Josep Lluís Carrion-i-Silvestre & Tomás del Barrio-Castro & Enrique López-Bazo, 2005. "Breaking the panels: An application to the GDP per capita," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 159-175, 07.
  19. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
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Cited by:

  1. Ke-Mei Chen & Te-Mu Wang, 2015. "Determinants of Poverty Status in Taiwan: A Multilevel Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 123(2), pages 371-389, September.

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