A Comparative Analysis of Wage Inequality in Korea and Japan Using UQR and Oaxaca-RIF Decomposition Method
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This paper purports to reveal the factors associated with wage inequality in Korea and Japan by using two micro panel data sets on households from 2014 to 2018, before COVID-19: Korea Labor & Income Panel Study (KLIPS) and Keio/Japan Household Panel Survey (KHPS/JHPS), respectively. This study employs an unconditional quantile regression (UQR) method to have robust estimation in measuring the wage inequality, as well as a recentered influence function (RIF)_Oaxaca decomposition method. The empirical results show that first, age, education, gender wage gap, dual structures of conglomerates vs. SMEs and regular vs. non-regular workers are the common sources of wage inequality in two countries. Second, in Japan, union members neither receive higher pay than non-union members nor have a smaller wage gap compared to their counterparts. However, they do in the middle and upper tails in Korea. Furthermore, an interesting finding lies in the relationship between unemployment and wages, which is that a higher unemployment rate contributes to a wage gap in Korea, while it does not have the same effect in Japan. Finally, the decomposition analysis suggests that the wage inequality is not sufficiently explained by the explanatory variables in each quantile of the two countries. Thus, this paper suggests that policy implication for resolving wage inequality should be associated with country-specific factors, including different institutions, industries, and social behaviors when establishing labor market-related policies.
Abstract
This paper purports to reveal the factors associated with wage inequality in Korea and Japan by using two micro panel data sets on households from 2014 to 2018, before COVID-19: Korea Labor & Income Panel Study (KLIPS) and Keio/Japan Household Panel Survey (KHPS/JHPS), respectively. This study employs an unconditional quantile regression (UQR) method to have robust estimation in measuring the wage inequality, as well as a recentered influence function (RIF)_Oaxaca decomposition method. The empirical results show that first, age, education, gender wage gap, dual structures of conglomerates vs. SMEs and regular vs. non-regular workers are the common sources of wage inequality in two countries. Second, in Japan, union members neither receive higher pay than non-union members nor have a smaller wage gap compared to their counterparts. However, they do in the middle and upper tails in Korea. Furthermore, an interesting finding lies in the relationship between unemployment and wages, which is that a higher unemployment rate contributes to a wage gap in Korea, while it does not have the same effect in Japan. Finally, the decomposition analysis suggests that the wage inequality is not sufficiently explained by the explanatory variables in each quantile of the two countries. Thus, this paper suggests that policy implication for resolving wage inequality should be associated with country-specific factors, including different institutions, industries, and social behaviors when establishing labor market-related policies.
참고문헌 (49)
- Akay, E. C., "What Do Conditional and Unconditional Quantile Regression Models Tell Us Something Different about Wage In-equality in Turkey?", Journal of Economic Culture and Society, 64, pp.257~277 (2021)
- Alejo, Javier, "Conditional vs. Unconditional Quantile Regression Models: A Guide to Practitioners", Economia, 44(88), pp.76~93 (2021)
- Autor David H., "Trends in U. S. Wage Inequality : Revising the Revisionists", Review of Economics and Statistics, 90, pp.300~323 (2008)
- Autor David H., "The Contribution of the Minimum Wage to US Wage Inequality over Three Decades : A Re-assessment", American Economic Journal : Applied Economics, 8(1), pp.58~99 (2016)
- Borgen, N. T., "Fixed Effects in Unconditional Quantile Regression", The Stata Journal, 16(2), pp.403~415 (2016)
- Buchinsky, M., "Changes in the U. S. Wage Structure 1963-1987 : Application of Quantile Regression", Econometrica, 62(2), pp.405~458 (1994)
- Cameron, Colin A., "Microeconometrics Using Stata" (2010), Stata Press
- Chen Z., "Globalization and Gender Wage In-equality in China", World Development, 44, pp.256~266 (2013)
- Cho, Jang-Ski, "College Graduate’s Determinants of Wage Applying Quantile Regression Model", Journal of Korean Data Analysis Society, 20(1), pp.237~246 (2018)
- Choi, Kang-Shik, "Does Unmeasured Ability Explain the Wage Premium Associated with Technological Change? Quantile Regression Analysis", Applied Economics, 39(9), pp.1163~1171 (2007)
- Choi, Yohan, "Temporary-permanent Contracts’ Wage Gap across the Wage Distribution in South Korea : Using Unconditional Quantile Regression with Individual Fixed Effects", Quarterly Journal of Labor Policy, 20(1), pp.1~28 (2020)
- DiNardo, John, "Labor Market Institution and the Distribution of Wages, 1973-1992 : A Semi-parametric Approach", Econometrica, 64(5), pp.1001~1044 (1996)
- Firpo, Sergio, "Unconditional Quantile Regressions", Econometrica, 77(3), pp.953~973 (2009)
- Hara, Hiromi, "The Gender Wage Gap across the Wage Distribution in Japan : within-and between-establishment Effects", Labour Economics, 53, pp.213~229 (2018)
- Heckman, J. J., "Sample Selection Bias as A Specification Error", Econometrica, 47, pp.153~161 (1979)
- Helpman, Elhanan, "Globalization and Inequality" (2018), Harvard University Press
- Huber, P., "Robust Statistics" (2009), Wiley
- Joe, D. H., "Minimum Wages and Wage Inequality in the OECD Countries", East Asian Economic Review, 24(3), pp.253~273 (2020)
- Jann, Ben, "The Blinder-Oaxaca Decomposition for Linear Regression Models", The Stata Journal, 8(4), pp.453~479 (2008)
- Juhn, Chinhui, "Wage Inequality and the Rise in Returns to Skill", Journal of Political Economy, 101(3), pp.410~442 (1993)
- Kambayashi, Ryo, "Minimum Wage in A Deflationary Economy : The Japanese Experience 1994-2003", Labour Economics, 24, pp.264~276 (2013)
- Kang, Seung-bok, "The Effect of the Minimum Wage on Employment Using Instrumental Variable", Korean Journal of Labor Economics, 40, pp.105~131 (2018)
- Katz, Lawrence F., "Changes in Relative Wages, 1963-1987: Supply and Demand Factors", Quarterly Journal of Economics, 107(1), pp.35~78 (1992)
- Kim, Dae-Il, "The Employment Effect of the Minimum Wage Hike in 2018 in South Korea", Korean Economic Review, 67(4), pp.1~35 (2019)
- Kim, J. Y., "A Comparison of Non-regular Employment in Korea and Japan : Nature, Difference, and Its Possible Reasons", Evolutionary and Institutional Economics Review, 6, pp.299~328 (2015)
- Koenker, R., "Regression Quantiles", Econometrica, 46(1), pp.33~50 (1978)
- Kunze, A., "Gender Wage Gap Studies : Consistency and Decomposition", Empirical Economics, 35, pp.63~76 (2006)
- Lee, Byung-Joo, "Quantile Regression Analysis of Wage De-terminants in the Korean Labor Market", Journal of the Korean Economy, 7(1), pp.1~31 (2006)
- Lee, David, "Wage Inequality in the United States during the 1980s: Rising Dispersion or Falling Minimum Wage?", Quarterly Journal of Economics, 114(3), pp.977~1023 (1980)
- Lee, Jung-Min, "The Effect of the Minimum Wage on Employment in Korea", Korea Journal of Labor Economics, 39(2), pp.1~34 (2016)
- Lemieux, Thomas, "Increasing Residual Wage Inequality Composition Effect, Noisy Data, Rising Demand for Skill?", American Economic Review, 96(3), pp.461~498 (2006)
- Lise, Jeremy, "Wage, Income and Consumption Inequality in Japan, 1981-2008 : From Boom to Lost Decades", Reviewof Economic Dynamics, 17(4), pp.582~612 (2014)
- Machado, J., "Counterfactual Decomposition of Changes in Wage Distributions Using Quantile Regression", Journal ofApplied Econometrics, 20, pp.445~465 (2005)
- Mincer, Jacob, "Schooling, Experience, and Earnings" (1974), Columbia University Press
- Newmark, D., "Employment Effects of Minimum and Sub-minimumWages : Panel Data on State MinimumWage Laws", Industrial Labor Relations Review, 46(1), pp.55~81 (1992)
- Reenen, John Van, "Wage Inequality, Technology and Trade : 21st Century Evidence", Labour Economics, 18(6), pp.730~741 (2011)
- Rios-Avila, Fernando, "Recentered Influence Functions(RIFs)in Stata : RIF Regression and RIF Decomposition", The Stata Journal, 20(1), pp.51~94 (2020)
- Seong, Jae-Min, "The Recent Trend and Causes of Wage Inequality", Monthly Labor Review, pp.55~74 (2018)
- Sitepu, H. R., "Regional Income Inequality Model Based on Theil Index Decomposition and Weighted Variance Coefficient", Journal of Physics: Conference Series, 983, pp.1~6 (2017)
- Tagami, Koto, "What Causes the Gender Wage Gap in Japan?", Japan Labor Issues, 7(42), pp.57~65 (2023)
- Yamaguchi, Kazuo, "Gender Inequality in Japanese Workplace and Employment : Theories and empirical evidence" (2019), Springer
- Wage Inequality and Cognitive Skills: Re-opening the De-bate, "Broecke, Stijn", National Bureau of Economic Research, Inc, ~, pp.No. 21965 (2016)
- Minimum Wages and Employment: A Case Study of the Fast Food Industry in New Jersey and Pennsylvania, "Card, D.", National Bureau of Economic Research, Inc, ~, pp.No. 4509 (1993)
- Effects of Increasing Non-regular Workers on Wage Distribution: An Application of RIF Regressions, "Choe, Chung", Bank of Korea, ~, pp.WP 2016-17 (2016)
- Minimum Wages and Productivity: An Overview and Evidence from Japan, "Morikawa, Masayuki", Research Institute of Economy, Trade and Industry (RIETI), ~, pp.No. 19-P-012 (2019)
- The Effects of Minimum Wages on Teenage Employment and Enrollment: Estimates from Matched CPS Data, "Newmark, D.", National Bureau of Economic Research, Inc, ~, pp.No. 5092 (1995)
- Labor Market Frictions, Self-employment and Productivity, "Poschk, Markus", McGill University, ~ (2017)
- What Happened to Wage Inequality in Japan during the last 25 Years? Evidence from the FFL Decomposition Method, "Yokoyama, Izumi", Research Institute of Economy, Trade and Industry (RIETI), ~, pp.16-E-081 (2016)
