Count data stochastic frontier models, with an application to the patents-R&D relationship
Abbreviated Journal Title
J. Prod. Anal.
Discrete data; Stochastic frontier analysis; Local maximum likelihood; Maximum simulated; likelihood; Halton sequence; LOCAL LIKELIHOOD ESTIMATION; PANEL-DATA; REGRESSION; HETEROGENEITY; INEFFICIENCY; EFFICIENCY; Business; Economics; Social Sciences, Mathematical Methods
This article introduces a new count data stochastic frontier model that researchers can use in order to study efficiency in production when the output variable is a count (so that its conditional distribution is discrete). We discuss parametric and nonparametric estimation of the model, and a Monte Carlo study is presented in order to evaluate the merits and applicability of the new model in small samples. Finally, we use the methods discussed in this article to estimate a production function for the number of patents awarded to a firm given expenditure on R&D.
Journal of Productivity Analysis
"Count data stochastic frontier models, with an application to the patents-R&D relationship" (2013). Faculty Bibliography 2010s. 3966.