We develop semiparametric and instrumental-variables approaches to self-selection problems in comparisons of wage inequality between educational groups. We propose new estimators to identify the causal effect of college education on scale parameters of wage distributions, using symmetry conditions on the joint distribution of outcome and selection errors, along with kernel weighting schemes. A ...

This paper investigates cost and profit efficiency of German hospitals. More specifically, it deals with the question how hospital efficiency varies with ownership, patient structure, and other exogenous factors, which are neither inputs nor outputs of the production process. We conduct a Stochastic Frontier Analysis (SFA) on a multifaceted administrative German dataset combined with the balanc...

This paper investigates cost and profit efficiency of German hospitals. More specifically, it deals with the question how hospital efficiency varies with ownership, patient structure, and other exogenous factors, which are neither inputs nor outputs of the production process. We conduct a Stochastic Frontier Analysis (SFA) on a multifaceted administrative German dataset combined with the balanc...

This paper presents Genetic Matching, a method of multivariate matching, that uses an evolutionary search algorithm to determine the weight each covariate is given. Both propensity score matching and matching based on Mahalanobis distance are limiting cases of this method. The algorithm makes transparent certain issues that all matching methods must confront. We present simulation studies that ...

This paper is concerned with developing uniform confidence bands for functions estimated nonparametrically with instrumental variables. We show that a sieve nonparametric instrumental variables estimator is pointwise asymptotically normally distributed. The asymptotic normality result holds in both mildly and severely ill-posed cases. We present an interpolation method to obtain a uniform confi...

This paper presents a Monte Carlo comparison of several versions of heteroscedasticity robust standard errors (HRSEs) to a nonparametric feasible generalized least squares procedure (NPGLS). Results suggest that the NPGLS procedure provides an improvement in efficiency ranging from 3% to 12% or more in reasonable sample sizes using simple functional forms for heteroscedasticity. This results in...

We introduce a class of instrumental quantile regression methods for heterogeneous treatment effect models and simultaneous equations models with nonadditive errors and offer computable methods for estimation and inference. These methods can be used to evaluate the impact of endogenous variables or treatments on the entire distribution of outcomes. We describe an estimator of the instrumental v...

We introduce a class of instrumental quantile regression methods for heterogeneous treatment effect models and simultaneous equations models with nonadditive errors and offer computable methods for estimation and inference. These methods can be used to evaluate the impact of endogenous variables or treatments on the entire distribution of outcomes. We describe an estimator of the instrumental v...

This paper uses a new non-parametric, unconditional, hyperbolic order-α quantile estimator to construct a hyperbolic version of the Malmquist index. Unlike traditional non-parametric efficiency estimators, the new estimator is both robust to data outliers and has a root-n convergence rate. We use this estimator to examine changes in the efficiency and productivity of U.S. banks between 1985 and...

i n the past decades, the effect of different tax amendments on various economic issues has been studied. the majority of these studies have avoided considering shadow economy as part of the calculation and analysis, and an issue, which has received little attention, is the relationship between green tax reforms and shadow economy, as for informal labor, which is well-connected to unemployment ...