The generalized panel data stochastic frontier model: A review and nonparametric estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F25%3A106249" target="_blank" >RIV/60460709:41110/25:106249 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s11123-025-00769-z?utm_source=getftr&utm_medium=getftr&utm_campaign=getftr_pilot&getft_integrator=clarivate" target="_blank" >https://link.springer.com/article/10.1007/s11123-025-00769-z?utm_source=getftr&utm_medium=getftr&utm_campaign=getftr_pilot&getft_integrator=clarivate</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11123-025-00769-z" target="_blank" >10.1007/s11123-025-00769-z</a>
Alternative languages
Result language
angličtina
Original language name
The generalized panel data stochastic frontier model: A review and nonparametric estimation
Original language description
Recently, the four component generalized stochastic frontier model has become increasingly common in practical applications. However, it remains tethered to potentially restrictive distributional assumptions on all four random components. In this paper, we show that when certain exogenous variables uniquely influence technology, time-varying inefficiency, or persistent inefficiency, all components of the model can be identified nonparametrically. In essence we require separability between the frontier, the conditional mean of time-varying inefficiency, and the conditional mean of persistent inefficiency. Given that our identification hinges on differencing, we recommend using splines or sieves to estimate each of the components of the model. We provide a short application to demonstrate the workings of the method.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50202 - Applied Economics, Econometrics
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
JOURNAL OF PRODUCTIVITY ANALYSIS
ISSN
0895-562X
e-ISSN
0895-562X
Volume of the periodical
64
Issue of the periodical within the volume
3
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
19
Pages from-to
321-339
UT code for WoS article
001540388700001
EID of the result in the Scopus database
2-s2.0-105012280507