Number of the records: 1
Dependence modeling in stochastic frontier analysis
- 1.0559340 - NHU-C 2023 RIV PL eng J - Journal Article
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
Institutional support: Cooperatio-COOP
Keywords : efficiency * productivity * panel data
OECD category: Applied Economics, Econometrics
Impact factor: 0.7, year: 2022
Method of publishing: 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.
Permanent Link: https://hdl.handle.net/11104/0332670
Number of the records: 1