Title

Count data stochastic frontier models, with an application to the patents-R&D relationship

Authors

Authors

E. Fe;R. Hofler

Comments

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Abbreviated Journal Title

J. Prod. Anal.

Keywords

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

Abstract

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 Title

Journal of Productivity Analysis

Volume

39

Issue/Number

3

Publication Date

1-1-2013

Document Type

Article

Language

English

First Page

271

Last Page

284

WOS Identifier

WOS:000318299000006

ISSN

0895-562X

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