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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fitting spatial stochastic frontier models in Stata

Kerui Du, Luis Orea, Inmaculada Álvarez Ayuso
3 citations
The Stata Journal Promoting communications on statistics and Stata
Spatial and Panel Data Analysis
3.39
article

Fitting spatial stochastic frontier models in Stata

Kerui Du, Luis Orea, Inmaculada Álvarez Ayuso
article en
3 citations

Abstract

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.

The Stata Journal Promoting communications on statistics and StataVol. 24(3)
Universidad de Oviedo (ES), Xiamen University (CN), Universidad Autónoma de Madrid (ES)
National Natural Science Foundation of China
Openalex Percentile: Top 6%
Spatial and Panel Data Analysis
3.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.