Dependence modeling in stochastic frontier analysis

This review covers several of the core methodological and empirical developments surrounding stochastic frontier models that incorporate various new forms of dependence. Such models apply naturally to panels where cross-sectional observations on firm productivity correlate over time, but also in sit...

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Bibliographic Details
Published in:Dependence modeling 2022-05, Vol.10 (1), p.123-144
Main Authors: Mamonov, Mikhail E., Parmeter, Christopher F., Prokhorov, Artem B.
Format: Article
Language:English
Subjects:
62H05
62J02
91B38
copulas
dependence
determinants of inefficiency
efficiency
endogeneity
panel data
productivity
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Summary:This review covers several of the core methodological and empirical developments surrounding stochastic frontier models that incorporate various new forms of dependence. Such models apply naturally to panels where cross-sectional observations on firm productivity correlate over time, but also in situations where various components of the error structure correlate between each other and with input variables. Ignoring such dependence patterns is known to lead to severe biases in the estimates of production functions and to incorrect inference.
ISSN:2300-2298
2300-2298
DOI:10.1515/demo-2022-0107