Decomposition of differences in distribution using quantile regression |
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| Institution: | 1. Department of Economics & Business, CRENoS, University of Cagliari, Via S. Ignazio, 78, 09123 Cagliari, Italy;2. CRENoS, University of Cagliari, Via S. Ignazio, 78, 09123 Cagliari, Italy;1. C3 IoT, Redwood City, CA, USA;2. University of California at Berkeley, Berkeley, USA;3. School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA;1. School of Economics and Management, Beihang University, Haidian, 100191 Beijing, China;2. School of Management Science and Engineering, Central University of Finance & Economics, Haidian, 100191 Beijing, China;1. Department of Urban Planning, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, Gyeonggi-do 448-701, Republic of Korea;2. Department of Economics, Kyung Hee University, 1 Hoegidong, Dongdaemoongu, 130-701 Seoul, Republic of Korea;1. School of Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, PR China;2. Research Center of Applied Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, PR China;3. Collaborative Innovation Center for Energy Economics and Energy Policy, China Institute for Studies in Energy Policy, Xiamen University, Fujian 361005, China |
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| Abstract: | This paper proposes a semiparametric estimator of distribution functions in the presence of covariates. The method is based on the estimation of the conditional distribution by quantile regression. The conditional distribution is then integrated over the range of covariates. Counterfactual distributions can be estimated, allowing the decomposition of changes in distribution into three factors: coefficients, covariates and residuals. Sources of changes in wage inequality in the USA between 1973 and 1989 are examined. Unlike most of the literature, we find that residuals account for only 20% of the explosion of inequality in the 80s. |
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