ESSAYS ON MICROECONOMETRICS AND LABOR ECONOMICS

Abstract

Studies of income inequality and intergenerational income mobility have important implications for policy. This dissertation consists of three essays which are contribute to the statistical inference on measures of intergenerational income mobility and the application of distributional decomposition to income inequality. The first two chapters propose semiparametric distribution regression estimators to study the transition matrices and local rank-rank slopes which are two measures of intergenerational income mobility. The third chapter extend the Oaxaca-Bliner decomposition to the distributions of income gap between two groups of people. The first chapter, INFERENCE ON COUNTERFACTUAL TRANSITION MATRICES, considers estimation and inference techniques for (i) conditional transition matrices -- transition matrices that are conditional on some vector of covariates, (ii) counterfactual transition matrices -- transition matrices that arise from holding fixed conditional transition matrices but adjusting the distribution of the covariates, and (iii) transition matrix average partial effects. Estimating conditional transition matrices is closely related to estimating conditional distribution functions, and we propose new semiparametric distribution regression estimators that may be of interest in other contexts as well. We also derive uniform inference results for transition matrices that allow researchers to account for issues such as multiple testing that naturally arise when estimating a transition matrix. We use our results to study differences in intergenerational mobility for black families and white families. In the application, we document large differences between the transition matrices of black and white families. We also show that these differences are partially, but not fully, explained by differences in the distributions of other family characteristics. The second chapter, SEMIPARAMETRIC ESTIMATION OF LOCAL RANK-RANK SLOPES, a local Rank-Rank slope which varies with parental rank and counterfactual Rank-Rank slope which adjusts for differences in the distribution of covariates. We develop new semiparametric distribution regression method to estimate those parameters. To make inference on different values of parental rank, we prove those estimators converge to Gaussian processes and build sup-t confidence bands by nonparametric bootstrap. In order to filter out some important observed characteristics, we sort the composition effects in an ascending order and propose classification analysis method, and also prove these converge to Gaussian processes. We apply our methods to study the differences in LRRS between cohort 79 and cohort 97. We show that the trend of LRRS of cohort 97 is very different from that of cohort 79 and find that children in cohort 97 which have larger composition effects are from higher income families, tend to be male and Nonblack and nonhispanic, and accept more years of education especially in advanced education. Also the difference in the parental education level after high school is unrelated to the composition effects across groups. The third chapter, DECOMPOSING WAGE GAPS BETWEEN HAN AND NON-HAN MINORITIES, uses CHIP 2013 dataset to analyze the income gap between two groups---Han and non-Han groups. Two methods are used in this paper to decompose the quantile differences of income among ethnic groups. One is distribution regression method proposed by y Chernozhukov, Fernández-Val, and Melly (2013) and the other is Recentered influence function regressions proposed by Firpo, Fortin, and Lemieux (2018). There are three main results of this paper. First, after decomposing, the income gap is larger in the low quantile than in high quantile. Second, income gap can be partly explained by composition effects although the structure effect account for a larger part of the total gap than composition effect at each quantile. Finally, education, region and age account for most proportion of composition effects, which due to the fact that most non-Han families are living in the poor area and thus do not have enough money to support their education. Most ethnic minorities live in rural areas where the economy is underdeveloped.