Dependence modeling in stochastic frontier analysis

0559340 - NHU-C 2023 RIV PL eng J - Článek v odborném periodiku
Mamonov, Mikhail - Parmeter, C. F. - Prokhorov, A.
Dependence modeling in stochastic frontier analysis.
Dependence Modeling. Roč. 10, č. 1 (2022), s. 123-144. ISSN 2300-2298
Institucionální podpora: Cooperatio-COOP
Klíčová slova: efficiency * productivity * panel data
Obor OECD: Applied Economics, Econometrics
Impakt faktor: 0.7, rok: 2022
Způsob publikování: Open access
https://doi.org/10.1515/demo-2022-0107

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.
Trvalý link: https://hdl.handle.net/11104/0332670