Semiparametric Estimation of Stochastic Production Frontier Models
Dados Bibliográficos
| ID | 19418367 |
|---|---|
| Autores | Yanqin Fan (University of Windsor), Qi Li (0000-0003-3042-3584, University of Guelph), Alfons Weersink (0000-0001-5081-3593, University of Guelph) |
| Ano | 1996 |
| Volume | 14 |
| Fascículo | 4 |
| Páginas | 460-468 |
| Data de publicação | 1996-10-01 |
| Peer Reviewed | Sim |
| Open Access | Não |
| Tipo | ARTICLE |
| Periódico | Journal of Business and Economic Statistics (JOURNAL) |
| Identificadores do periódico | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Editora | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.1996.10524675 |
| OpenAlex | W2083530934 |
| Idioma | EN |
| Citações recebidas | 16 |
| Referências citadas | 25 |
This article extends the linear stochastic frontier model proposed by Aigner, Lovell, and Schmidt to a semiparametric frontier model in which the functional form of the production frontier is unspecified and the distributions of the composite error terms are of known form. Pseudolikelihood estimators of the parameters characterizing the two error terms of the model are constructed based on kernel estimation of the conditional mean function. The Monte Carlo results show that the proposed estimators perform well in finite samples. An empirical application is presented. Extensions to a partially linear frontier function and to more flexible one-sided error distributions than the half-normal are discussed
Conditional expectation · Econometrics · Economics · Estimator · Frontier · Kernel density estimation · Monte Carlo method · Semiparametric model · Semiparametric regression · Statistics · Economic Growth and Productivity · Efficiency Analysis Using DEA · Global trade and economics · Mathematics · Applied Mathematics
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| Obras citantes distintas | 16 |
|---|---|
| Citações por ano | 0,67 |
| Intervalo de citações | 2002 - 2026 (25) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 15 |