A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers
By Anthony J. Glass, Karligash Kenjegalieva, Robin C. Sickles. 2015
176 citations recorded by the source corpus.
By blending seminal literature on non-spatial stochastic frontier models with key contributions to spatial econometrics we develop a spatial autoregressive (SAR) stochastic frontier for panel data. The specification of the SAR frontier allows efficiency to vary over time and across the cross-sections. Efficiency is calculated from a composed error structure by assuming a half-normal distribution for inefficiency. The SAR frontier is estimated using maximum likelihood methods taking into account the endogenous SAR variable. The application of the estimator to an aggregate production frontier for European countries highlights, among other things, the asymmetry between efficiency spillovers to and from a country.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/f0c8dbd1cbec14c136826e7de3cf16948f8abfed
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In Economics and Econometrics
- Inmaculada C Álvarez
- Luis Orea
- William H. Greene
- Lourdes Trujillo
- N. Key
- MarI´a Manuela González
- Tim Coelli
- C. O'Donnell
Citations in the corpus
- A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms (2019, methodology): “In this sense, a spatial autoregressive (SAR) version of our spatial SF model can also be viewed as an extension of the Glass et al. (2016a) model.”