Consistent estimation of the fixed effects stochastic frontier model

By Y. Chen, P. Schmidt, Hung-Jen Wang. 2014

185 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/4b207e1a7bff28ca333392030dcdbd140c82480b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Christopher F. Parmeter
2. Robin C. Sickles
3. Federico Belotti
4. Giuseppe Ilardi
5. Karligash Kenjegalieva
6. Anthony J. Glass
7. Subal C. Kumbhakar
8. William H. Greene

In Management Science and Operations Research

1. Christopher F. Parmeter
2. Federico Belotti
3. Giuseppe Ilardi
4. Robin C. Sickles
5. Subal C. Kumbhakar
6. Karligash Kenjegalieva
7. Anthony J. Glass
8. William H. Greene

Citations in the corpus

• Persistent and transient productive inefficiency: a maximum simulated likelihood approach (2015, unknown): “The characteristics of the TFE model have been examined in some recent studies, such as Chen et al. (2014) who develop an ML estimator based on likelihood function that applies after the ‘within groups’ transformation removes hi.”
• Efficiency Analysis: A Primer on Recent Advances (2014, methodology): “First, Chen et al. (2014) proposed a solution in the fixed-effects framework. Following a theorem in Domı́nguez-Molina, GonzálezFaŕıas & Ramos-Quiroga (2003), they showed that the likelihood function of the within transformed and the first-difference model have closed form expressions. The same theo”
• A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers (2015, background): “See Chen et al. (2014) for a non-spatial stochastic frontier model with consistent estimates of the xed e¤ects, and Greene (2005) for a non-spatial stochastic frontier model with random e¤ects.17 We do, however, account for spatial heterogeneity via the SAR variable in the SARF and the SDF.”
• Consistent inference in fixed-effects stochastic frontier models (2017, methodology): “Following Gouriéroux & Monfort (1991), under the regularity conditions ensuring the large sample properties of the MMLE, the resulting marginal maximum simulated likelihood estimator (MMSLE) is consistent and asymptotically equivalent to the MMLE as n→∞ and G→∞ with √ n/G→ 0.12 It then follows that”