Wage Gap and Employment Status in Indian Labour Market Quantile Based Counterfactual Analysis

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Panchanan Das

Abstract

This study examines the extent of wage gap between workers in permanent and temporary jobs but in roughly similar occupation types by evaluating the impact of workers’ characteristics and education. The differential effects of the covariates on wage gap at different locations of the wage distribution are estimated by applying quantile regression model. After estimating the differential effects the relevance of glass ceiling or sticky floor hypothesis has been tested with Indian data. The wage gap between temporary and permanent employment is decomposed into endowment effect based on the difference in labour market characteristics and coefficient effect based on the difference in returns for the same characteristics. The study observes that the wage gap between temporary and permanent workers is wider at the upper tail of the distribution not rejecting the glass ceiling hypothesis. The decomposition analysis suggests that the wage gap presents in the Indian labour market primarily because of discrimination measured by the coefficients effects.

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Das, P. (2018). Wage Gap and Employment Status in Indian Labour Market. World Journal of Applied Economics, 4(2), 117-134. https://doi.org/10.22440/wjae.4.2.4
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References

Ahmed, S., & McGillivray, M. (2015). Human Capital, Discrimination, and the Gender Wage Gap in Bangladesh. World Development, 67 , 506-524. http://dx.doi.org/10.1016/j.worlddev.2014.10.017

Banerjee, A., & Piketty, T. (2005). Top Indian Incomes, 1922-2000. World Bank Economic Review, 19 (1), 1-20. http://dx.doi.org/10.1093/wber/lhi001

Chancel, L., & Piketty, T. (2017). Indian income inequality, 1922-2014 From British Raj to Billionaire Raj? (Working Paper Series No. 11). World Inequality Database. http://wid.world/document/chancelpiketty2017widworld/.

Chi, W., & Li, B. (2014). Trends in China's Gender Employment and Pay Gap: Estimating Gender Pay Gaps with Employment Selection. Journal of Comparative Economics, 42 (3), 708- 725. http://dx.doi.org/10.1016/j.jce.2013.06.008

Cohn, E., & Addison, J. T. (1997). The Economic Returns to Lifelong Learning (Working Paper No. B-97-04). Division of Research, University of South Carolina College of Business Administration.

Firpo, S., Fortin, N., & Lemieux, T. (2009). Unconditional Quantile Regressions. Econo- metrica, 77 (3), 953-973. http://dx.doi.org/10.3982/ECTA6822

Fortin, N., Lemieux, T., & Firpo, S. (2011). Decomposition Methods in Economics. In O. Ashenfelter & D. Card (Eds.), Handbook of labor economics, (4a) (p. 1-102). Elsevier, Amsterdam.

Gonzalez, X., & Miles, D. (2001). Wage Inequality in a Developing Country: Decrease in Minimum Wage or Increase in Education Returns. Empirical Economics, 1 (26), 135-148. http://dx.doi.org/10.1007/s001810000056

Gottschalk, P., & Smeeding, T. (1997). Cross-national Comparisons of Earnings and Income Inequality. Journal of Economic Literature, 2 (35), 633-687.

Hendricks, W., & Koenker, R. (1992). Hierarchical Spline Models for Conditional Quantiles and the Demand for Electricity. Journal of the American Statistical Association, 417 (87), 58-68. http://dx.doi.org/10.2307/2290452

Juhn, C., Murphy, K., & Pierce, B. (1993). Wage Inequality and the Rise in Returns to Skill. Journal of Political Economy, 3 (101), 410-441. http://dx.doi.org/10.1086/261881

Koenker, R., & Bassett, G. (1978). Regression Quantiles. Econometrica, 1 (46), 33-50. http://dx.doi.org/10.2307/1913643

Koenker, R., & Bassett, G. (1982). Robust Tests for Heteroscedasticity Based on Regression Quantiles. Econometrica, 1 (50), 43-61. http://dx.doi.org/10.2307/1912528

Lechmann, D. S., & Schnabel, C. (2012). Why is There a Gender Earnings Gap in Self-employment? A Decomposition Analysis with German Data. IZA Journal of European Labor Studies, 6 (1), 1-25. http://dx.doi.org/10.1186/2193-9012-1-6

Levy, F., & Murmane, R. J. (1992). U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations. Journal of Economic Literature, 3 (30), 1333-1381.

Machado, J., & Mata, J. (2005). Counterfactual Decompositions of Changes in Wage Distributions Using Quantile Regression. Journal of Applied Econometrics, 4 (20), 445-465. http://dx.doi.org/10.1002/jae.788

Magnani, E., & Zhu, R. (2012). Gender Wage Differentials among Rural-urban Migrants in China. Regional Science and Urban Economics, 5 (42), 779-793. http://dx.doi.org/10.1016/j.regsciurbeco.2011.08.001

Melly, B. (2005). Decomposition of Differences in Distribution using Quantile Regression. Labour Economics, 4 (12), 577-590. http://dx.doi.org/10.1016/j.labeco.2005.05.006

Mueller, R. (2000). Public- and Private-Sector Wage Differentials in Canada Revisited. Industrial Relations, 3 (39), 375-400. http://dx.doi.org/10.1111/0019-8676.00173

Naticchioni, P., Ricci, A., & Rustichelli, E. (2008). Wage Inequality, Employment Structure and Skill-biased Change in Italy. Labour, s1 (22), 27-51. http://dx.doi.org/10.1111/j.1467-9914.2008.00416.x

Oaxaca, R. (1973). Male-female Wage Differential in Urban Labour Market. International Economic Review, 3 (14), 693-709. http://dx.doi.org/10.2307/2525981

Picchio, M. (2006). Wage Differentials and Temporary Jobs in Italy (UCL Discussion Paper No. 33). Departement des Sciences Economiques. https://pure.uvt.nl/ws/portalfiles/portal/1439134/2006-33.pdf.

Poterba, J. M., & Rueben, K. S. (1994). The Distribution of Public Sector Wage Premia: New Evidence Using Quantile Regression Methods (Working Paper No. 4734). NBER. http://dx.doi.org/10.3386/w4734

Skyt Nielsen, H., & Rosholm, M. (2001). The Public-private Sector Wage Gap in Zambia? A Quantile Regression Approach. Empirical Economics, 1 (26), 169-182. http://dx.doi.org/10.1007/s001810000051