ﻻ يوجد ملخص باللغة العربية
We analyze the sources of changes in the distribution of hourly wages in the United States using CPS data for the survey years 1976 to 2019. We account for the selection bias from the employment decision by modeling the distribution of annual hours of work and estimating a nonseparable model of wages which uses a control function to account for selection. This allows the inclusion of all individuals working positive hours and provides a fuller description of the wage distribution. We decompose changes in the distribution of wages into composition, structural and selection effects. Composition effects have increased wages at all quantiles but the patterns of change are generally determined by the structural effects. Evidence of changes in the selection effects only appear at the lower quantiles of the female wage distribution. These various components combine to produce a substantial increase in wage inequality.
We examine the impact of annual hours worked on annual earnings by decomposing changes in the real annual earnings distribution into composition, structural and hours effects. We do so via a nonseparable simultaneous model of hours, wages and earning
We develop a distribution regression model under endogenous sample selection. This model is a semiparametric generalization of the Heckman selection model that accommodates much richer patterns of heterogeneity in the selection process and effect of
We develop a new approach for estimating average treatment effects in the observational studies with unobserved group-level heterogeneity. A common approach in such settings is to use linear fixed effect specifications estimated by least squares regr
We consider a situation where the distribution of a random variable is being estimated by the empirical distribution of noisy measurements of that variable. This is common practice in, for example, teacher value-added models and other fixed-effect mo
This paper provides a method to construct simultaneous confidence bands for quantile functions and quantile effects in nonlinear network and panel models with unobserved two-way effects, strictly exogenous covariates, and possibly discrete outcome va