We consider the identification of counterfactual distributions and treatment effects when the outcome variables and conditioning covariates are observed in separate data sets. Under the standard selection on observables assumption, the counterfactual distributions and treatment effect parameters...

This paper constructs a consistent model specification test based on the difference between the nonparametric kernel sum of squares of residuals and the sum of squares of residuals from a parametric null model. We establish the asymptotic normality of the proposed test statistic under the null...

This paper extends the linear stochastic frontier model proposed by D. J. Aigner, C. A. K. Lovell, and P. Schmidt (1977) to a semiparametric frontier model in which the functional form of the production frontier is unspecified and the distributions of the composite error terms are of known form....

Let <italic>F</italic> denote a distribution function defined on the probability space (Ω,null,<italic>P</italic>), which is absolutely continuous with respect to the Lebesgue measure in <italic>R</italic> with probability density function <italic>f</italic>. Let <italic>f</italic>₀(·,β) be a parametric density function that depends on an unknown <italic>p</italic> × 1 vector β. In this...

Research in empirical health economics has found that the relationship between medical expenditures and age, income and other variables can be highly nonlinear. Moreover, men and women can have quite different medical expenditure patterns due to their differences in life expectancy. Thus it may...

The focus of this paper is the nonparametric estimation of an instrumental regression function f defined by conditional moment restrictions that stem from a structural econometric model E[Y − f (Z) | W] = 0, and involve endogenous variables Y and Z and instruments W. The function f is the...

Copulas are functions that describe the dependence between two or more random variables. This article provides a brief review of copula theory and two areas of economics in which copulas have played important roles: multivariate modeling and partial identification of parameters that depend on...

In this paper, we establish sharp bounds on the joint distribution of potential outcomes and the distribution of treatment effects in parametric switching regime models with normal mean-variance mixture errors and in the semi-parametric switching regime models of <xref ref-type="bibr" rid="R30">Heckman (1990)</xref>. Our results for...

In this paper, we explore partial identification and inference for the quantile of treatment effects for randomized experiments. First, we propose nonparametric estimators of sharp bounds on the quantile of treatment effects and establish their asymptotic properties under general conditions....