This paper introduces a new data set for the analysis of productivity in U.S. manufacturing. It consists of data on production and input levels when the plants in an industry operate at capacity. The estimates are consistent with those obtained using data on actual operations from the ASM. As an...

This paper shows how to construct locally robust semiparametric GMM estimators, meaning equivalently moment conditions have zero derivative with respect to the first step and the first step does not affect the asymptotic variance. They are constructed by adding to the moment functions the...

In this paper, we compare two fundamentally different judgmental demand forecasting approaches used to estimate demand and their corresponding demand distributions. In the first approach, parameters are obtained from a linear regression and maximum likelihood estimation (MLE) based on team...

In this paper, we consider the stochastic ray production function that has been revived recently by Henningsen et al. (2017). We use a profit-maximizing framework to resolve endogeneity problems that are likely to arise, as in all distance functions, and we derive the system of equations after...

We give a general construction of debiased/locally robust/orthogonal (LR) moment functions for GMM, where the derivative with respect to first step nonparametric estimation is zero and equivalently first step estimation has no effect on the influence function. This construction consists of...

Let H 0 (X) be a function that can be nonparametrically estimated. Suppose E [ Y | X ]= F 0 [ X ß 0 H 0 (X) ] . Many models fit this framework, including latent in- dex models with an endogenous regressor and nonlinear models with sample se- lection. We show that the vector ß 0 and unknown...

In this study, we provide a guideline for dealing with endogenous inputs and environmental variables in Battese and Coelli's (1995) stochastic frontier model. Our Monte Carlo simulations show that our estimators perform well

This study provides a guideline for dealing with endogenous inputs and environmental variables in Battese and Coelli's (1995) stochastic frontier model, which has been used in a vast number of empirical studies. The presence of endogenous variables in Battese and Coelli's model leads to...

This paper uses a directional output distance function to estimate a multi-output production frontier for a sample of experimental plots grown for the Sustainable Agriculture Farming Systems project at the University of California, Davis. Cross-sectional technical efficiency indices are...

This paper aims to provide empirical researchers with an overview of the methodological issues that arise when estimating total factor productivity at the establishment level, as well as of the existing (parametric and semiparametric) techniques designed to overcome them. Apart from the...