Nonparametric estimation of the determinants of inefficiency

Christopher Parmeter, Hung-Jen Wang () and Subal Kumbhakar

Journal of Productivity Analysis, 2017, vol. 47, issue 3, No 3, 205-221

Abstract: Abstract We consider the benchmark stochastic frontier model where inefficiency is directly influenced by observable determinants. In this setting, we estimate the stochastic frontier and the conditional mean of inefficiency without imposing any distributional assumptions. To do so we cast this model in the partly linear regression framework for the conditional mean. We provide a test of correct parametric specification of the scaling function. An empirical example is also provided to illustrate the practical value of the methods described here.

Keywords: Partly linear; Heteroskedasticity; Kernel; Bandwidth (search for similar items in EconPapers)
JEL-codes: C13 C14 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (23)

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DOI: 10.1007/s11123-016-0479-x

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