Nonparametric frontier analysis using Stata
Abstract. In this article, we describe five new Stata commands that fit and provide
statistical inference in nonparametric frontier models. The tenonradial
and teradial commands fit data envelopment models where nonradial and
radial technical efficiency measures are computed (Färe, 1998,
Fundamentals of Production Theory; Färe and Lovell, 1978,
Journal of Economic Theory 19: 150–162; Färe, Grosskopf, and
Lovell, 1994a, Production Frontiers). Technical efficiency measures are
obtained by solving linear programming problems. The teradialbc,
nptestind, and nptestrts commands provide tools for making
statistical inference regarding radial technical efficiency measures (Simar and
Wilson, 1998, Management Science 44: 49–61; 2000, Journal of
Applied Statistics 27: 779–802; 2002, European Journal of
Operational Research 139: 115–132). We provide a brief overview of
the nonparametric efficiency measurement, and we describe the syntax and
options of the new commands. Additionally, we provide an example showing the
capabilities of the new commands. Finally, we perform a small empirical study
of productivity growth.
View all articles by these authors:
Oleg Badunenko, Pavlo Mozharovskyi
View all articles with these keywords:
tenonradial, teradial, teradialbc, nptestind, nptestrts, nonparametric efficiency analysis, data envelopment analysis, technical efficiency, radial measure, nonradial measure, linear programming, bootstrap, subsampling bootstrap, smoothed bootstrap, bias correction, frontier analysis
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