2012
DOI: 10.2139/ssrn.2045474
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Consistent Estimation of the 'True' Fixed-Effects Stochastic Frontier Model

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Cited by 22 publications
(17 citation statements)
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“…This has a critical impact on the SF analysis since an accurate estimation of inefficiency scores relies on the precision of these estimates. Belotti and Ilardi [19] show that the incidental variable problem vanishes in long panel ( ≥ 15).…”
Section: Estimation Methodsmentioning
confidence: 98%
“…This has a critical impact on the SF analysis since an accurate estimation of inefficiency scores relies on the precision of these estimates. Belotti and Ilardi [19] show that the incidental variable problem vanishes in long panel ( ≥ 15).…”
Section: Estimation Methodsmentioning
confidence: 98%
“…Pooled‐panel models can generate a misspecification bias in presence of unobserved time‐invariant variables (Belotti & Ilardi, ). Greene () addressed this problem with unit‐specific intercepts.…”
Section: Methodsmentioning
confidence: 99%
“…First, one has to solve the incidental parameters problem, which appears when the panel length is small compared with the number of subjects, causing inconsistent estimation. As Belotti and Ilardi () show, the dummy variable approach for estimation is only suitable when the panel length is over 10. Our sample is highly unbalanced because of the attrition of farmers and contains observations only at four points in time.…”
Section: Methodsmentioning
confidence: 99%
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“…In addition, the unit-specific intercepts can be inconsistently estimated in panel data characterised by large N and short observation periods, due to the incidental parameter problem (Neyman and Scott, 1948;Lancaster, 2002). In this respect, Belotti and Ilardi (2012) recently demonstrated that the inconsistency bias is negligible in samples with longer than 10 years, thus allowing the validation of our empirical strategy, which relies on the TFE model 11 . With respect to the possible modelling choice of the inefficiency term as a time variant or invariant process, considering that our dataset includes a rather long period of observations ( ), a time-varying specification seems to be the most plausible choice.…”
Section: Argues That If "A Sufficient Number Of Auxiliary Variables Tmentioning
confidence: 99%