Fitting spatial stochastic frontier models in Stata
In this article, we introduce a new command, xtsfsp, for fitting spatial stochastic frontier models in Stata. Over the last decades, stochastic frontier models have seen important theoretical progress via the incorporation of various types of spatial components. Models that can account for spatial dependence and spillovers have been developed for efficiency and productivity analysis, drawing extensive attention from industry and academia. Because of the unavailability of the statistical packages, the empirical applications of the new stochastic frontier models appear to be lagging. The xtsfsp command provides a procedure for fitting spatial stochastic frontier models in the style of Orea and Álvarez (2019, Journal of Econometrics 213: 556-577) and Galli (2023, Spatial Economic Analysis 18: 239-258), enabling users to handle different sources of spatial dependence. In this article, we introduce spatial stochastic frontier models, describing the syntax and options of the new command and providing several examples to illustrate its usage.
Authors
- Kerui Du (ORCID: https://orcid.org/0000-0001-7388-7018)
- Luis Orea (ORCID: https://orcid.org/0000-0003-1146-9261)
- Inmaculada Álvarez Ayuso (ORCID: https://orcid.org/0000-0003-0495-623X)
Institutions
- Universidad de Oviedo (ES)
- Xiamen University (CN)
- Universidad Autónoma de Madrid (ES)
Publication Details
- Journal
- The Stata Journal Promoting communications on statistics and Stata
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1177/1536867x241276109
- Citations
- 3
- Primary Topic
- Spatial and Panel Data Analysis
- Type
- article
- Field-Weighted Citation Impact
- 3.39
Funders
- National Natural Science Foundation of China