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...

This paper takes a fresh look at the impact of financial development on economic growth by using recently developed kernel methods that allow for heterogeneity in partial effects, nonlinearities and endogenous regressors. Our results suggest that while the positive impact of financial...

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, 'partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple...

This note takes a first look at the distribution of returns to education for people with disabilities, a particularly disadvantaged group whose labor market performances have not been well studied or documented. Using a nonparametric approach, we uncover significant heterogeneity in the returns...

Economic conditions such as convexity, homogeneity, homotheticity, and monotonicity are all important assumptions or consequences of assumptions of economic functionals to be estimated. Recent research has seen a renewed interest in imposing constraints in nonparametric regression. We survey the...

This paper relaxes the assumption of homogeneous rates of return to schooling by employing nonparametric kernel regression. This approach allows us to examine the differences in rates of return to education both across and within groups. Similar to previous studies we find that on average blacks...