In this paper we consider estimation and inference of common breaks in panel data models via adaptive group fused lasso. We consider two approaches -- penalized least squares (PLS) for first-differenced models without endogenous regressors, and penalized GMM (PGMM) for first-differenced models...

In this paper, we employ a partially linear nonparametric additive regression estimator, with recent U.S. Current Population Survey data, to analyze returns to schooling. Similar to previous research, we find that blacks and Hispanics have higher rates of return on average. However, for married...

In this article we overview nonparametric (spline and kernel) regression methods and illustrate how they may be used in labor economic applications. We focus our attention on issues commonly found in the labor literature such as how to account for endogeneity via instrumental variables in a...

Nonparametric estimators provide a flexible means of uncovering salient features of auction data. Although these estimators are popular in the literature, many key features necessary for proper implementation have yet to be uncovered. Here we provide several suggestions for nonparamteric...