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Exploring the Urban-Rural Labor Income Gap in Uruguay: A Quantile Regression Decomposition

Author

Listed:
  • Marcelo Bergolo

    (Center for Distributive Labor and Social Studies (CEDLAS), Universidad Nacional de La Plata, Argentina and the National Scientific and Technical Research Council (CONICET), Argentina.)

  • Fedora Carbajal

    (Center for Distributive Labor and Social Studies (CEDLAS), Universidad Nacional de La Plata, Argentina and the National Scientific and Technical Research Council (CONICET), Argentina.)

Abstract

This paper analyzes the differences in real hourly labor income (RHLI) distributions between urban and rural workers for Uruguay in 2006. A quantile regression decomposition technique is applied in order to examine the urban-rural gap across the entire RHLI distribution. The urban-rural gap was primarily explained by the differences in the distribution of covariates along the entire distribution. Differences in distribution of returns favored the rural workers in most of the RHLI distribution although its contribution decreased across quantiles. The resulting gap in returns was most relevant for the worst off rural workers compared to the urban counterparts in both Montevideo and the rest of the urban centers.

Suggested Citation

  • Marcelo Bergolo & Fedora Carbajal, 2010. "Exploring the Urban-Rural Labor Income Gap in Uruguay: A Quantile Regression Decomposition," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 25(2), pages 133-168, Diciembre.
    • Handle: RePEc:ila:anaeco:v:25:y:2010:i:2:p:133-168
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    1. Chamarbagwala, Rubiana, 2006. "Economic Liberalization and Wage Inequality in India," World Development, Elsevier, vol. 34(12), pages 1997-2015, December.
    2. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-1044, September.
    3. Daniel Miles & Máximo Rossi, 1999. "Geographic concentration and structure of wages in developing countries: the case of Uruguay," Documentos de Trabajo (working papers) 1399, Department of Economics - dECON.
    4. Henry Overman & Patricia Rice & Anthony Venables, 2010. "Economic Linkages across Space," Regional Studies, Taylor & Francis Journals, vol. 44(1), pages 17-33.
    5. Liu, Zhiqiang, 2005. "Institution and inequality: the hukou system in China," Journal of Comparative Economics, Elsevier, vol. 33(1), pages 133-157, March.
    6. Raimundo Soto & Arístides Torche, 2004. "Spatial Inequality, Migration and Economic Growth in Chile," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 41(124), pages 401-424.
    7. Shilpi, Forhad, 2008. "Migration, sorting and regional inequality : evidence from Bangladesh," Policy Research Working Paper Series 4616, The World Bank.
    8. Bayer, Patrick & Keohane, Nathaniel & Timmins, Christopher, 2009. "Migration and hedonic valuation: The case of air quality," Journal of Environmental Economics and Management, Elsevier, vol. 58(1), pages 1-14, July.
    9. Ravi Kanbur & Hillel Rapoport, 2005. "Migration selectivity and the evolution of spatial inequality," Journal of Economic Geography, Oxford University Press, vol. 5(1), pages 43-57, January.
    10. Rubiana Chamarbagwala, 2010. "Economic liberalization and urban–rural inequality in India: a quantile regression analysis," Empirical Economics, Springer, vol. 39(2), pages 371-394, October.
    11. Guillermo Alves & Verónica Amarante & Gonzalo Salas & Andrea Vigorito, 2012. "La desigualdad del ingreso en Uruguay entre 1986 y 2009," Documentos de Trabajo (working papers) 12-03, Instituto de Economía - IECON.
    12. Caridad Araujo, 2004. "Can Non-Agricultural Employment Reduce Rural Poverty? Evidence from Mexico," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 41(124), pages 383-399.
    13. Marcelo Bérgolo & Fedora Carbajal, 2008. "Brecha Urbano - Rural de Ingresos Laborales en Uruguay para el Año 2006: Una Descomposición por Cuantiles," CEDLAS, Working Papers 0075, CEDLAS, Universidad Nacional de La Plata.
    14. Kanbur, Ravi & Venables, Anthony J., 2003. "Spatial Inequality and Development," Working Papers 127779, Cornell University, Department of Applied Economics and Management.
    15. Nguyen, Binh T. & Albrecht, James W. & Vroman, Susan B. & Westbrook, M. Daniel, 2007. "A quantile regression decomposition of urban-rural inequality in Vietnam," Journal of Development Economics, Elsevier, vol. 83(2), pages 466-490, July.
    16. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.
    17. Buchinsky, Moshe, 1994. "Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression," Econometrica, Econometric Society, vol. 62(2), pages 405-458, March.
    18. Rodrigo García Verdú, 2005. "Income, Mortality, and Literacy Distribution Dynamics Across States in Mexico: 1940-2000," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 42(125), pages 165-192.
    19. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    20. Leonardo Gasparini & Guillermo Cruces & Leopoldo Tornarolli & Mariana Marchionni, 2009. "A Turning Point? Recent Developments on Inequality in Latin America and the Caribbean," CEDLAS, Working Papers 0081, CEDLAS, Universidad Nacional de La Plata.
    21. Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-442, June.
    22. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    23. Marcel Fafchamps & Forhad Shilpi, 2005. "Cities and Specialisation: Evidence from South Asia," Economic Journal, Royal Economic Society, vol. 115(503), pages 477-504, April.
    24. Javier Escobal & Maximo Torero, 2003. "Adverse Geography and Differences in Welfare in Peru," WIDER Working Paper Series DP2003-73, World Institute for Development Economic Research (UNU-WIDER).
    25. Raimundo Soto & Aristides Torche, 2004. "Spatial Inequality in Chile," Econometric Society 2004 Latin American Meetings 241, Econometric Society.
    26. Ravi Kanbur & Luis López & Anthony J Venables, 2005. "Symposium on Spatial Inequality in Latin America," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 42(125), pages 133-136.
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    More about this item

    Keywords

    Urban-rural gap; labor income; quantile regression decomposition; Uruguay. JEL Classification: C15; J31; O18.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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