This paper evaluates the performance of three bootstrap algorithms for the data envelopment analysis (DEA) estimator using a Monte Carlo simulation study. The Löthgren and Tambour (1997) (LT) algorithm; the Simar and Wilson (1997b) (SW) algorithm; and a combination of the LT and SW algorithms...

This paper studies performance of both point and interval predictors of technical inefficiency in the stochastic production frontier model using a Monte Carlo experiment. In point prediction we use the Jondrow et al. (1980) point predictor of technical inefficiency, while for interval prediction...

This paper has two purposes. The first purpose is methodological and aims to extend previous work on efficiency analysis by implementing a multiple-output stochastic ray frontier production function model. This model generalizes the single-output stochastic frontier model to multiple-input,...

This paper proposes a generalization of the single output stochastic production frontier model. The generalization allows estimation of production frontiers and distance functions (technical efficiency) for multiple output technologies using cross section or panel data on inputs and outputs.

We demonstrate that panel unit root tests can have high power when a small fraction of the series are stationary and may lack power when a large fraction is stationary. The acceptance or rejection of the null is thus not sufficient evidence to conclude that all series have a unit root or that...

The double bootstrap provides a useful tool for bootstrapping approximately pivotal quantities by using an "inner" bootstrap loop to estimate the variance. When the estimators are computationally intensive, the double bootstrap may become infeasible. We propose the use of a new variance...