Kernel density estimation for multivariate data is an important technique that has a wide range of applications in econometrics and finance. However, it has received significantly less attention than its univariate counterpart. The lower level of interest in multivariate kernel density...

This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when selection to treatment is based on observable characteristics. The paper also presents three estimation procedures for these parameters, all of which have two steps: a...

This paper examines the performance of the U.S.~commercial banking industry over 1984--2002. Rather than measuring performance relative to the unknown (and difficult-to-estimate) boundary of the production set, performance for a given bank is measured relative to {\it expected} maximum output...

This paper investigates the process by which a cohort of males accumulate human capital via formal education and labor market participation. I use all available annual waves of the 1979 youth cohort of the National Longitudinal Survey of Labor Market Experience (NLSY79) to estimate a dynamic...

Propensity score matching is becoming increasingly common in clinical medicine, demographic and economic research for the evaluation of the magnitude of treatment effects. Existing studies generally use parametric estimators of binary response models such as the probit and logit to estimate the...

It has been a conventional wisdom that the two-sample version of the goodness-of-fit test like the Kolmogorov-Smirnov, Cramér-von Mises and Anderson-Darling tests fail to have good power particularly against very specific alternatives. We show that a modified version of Neyman Smooth test that...

In order to forecast one-step ahead volatility, we calculated jump intensity by using estimated parameters of a duration model of price change. In this procedure, we do not assume any distribution on log-return. Although we do not make any distributional assumption, we may practically choose a...

This paper studies the estimation of a class of copula-based semiparametric stationary Markov models. These models are characterized by nonparametric invariant (or marginal) distributions and parametric copula functions that capture the temporal dependence of the processes; the implied...

We estimate the effect of training quality on earnings using a Peruvian program, which targets disadvantaged youths. The identification of causal effects is possible because of two attractive features in the data. First, selection of training courses is based on public bidding processes that...

Traditional instrumental variable estimators do not generally estimate effects for the treated population but for the unobserved population of compliers. They do identify effects for the treated when there is one-sided perfect non-compliance. However, this property is lost when covariates are...