Nonparametric frontier analysis using Stata

Oleg Badunenko, Pavlo Mozharovskyi

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    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.
    Original languageEnglish
    Pages (from-to)550-589
    JournalThe Stata Journal
    Volume16
    Issue number3
    Publication statusPublished - 16 Sep 2016

    Keywords

    • st0001
    • 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

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