{"title":"Fitting spatial stochastic frontier models in Stata","authors":"Kerui Du, Luis Orea, Inmaculada C. Álvarez","doi":"10.1177/1536867x241276109","DOIUrl":null,"url":null,"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.","PeriodicalId":501101,"journal":{"name":"The Stata Journal: Promoting communications on statistics and Stata","volume":"35 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Stata Journal: Promoting communications on statistics and Stata","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1536867x241276109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.
在本文中,我们将介绍一个新命令--xtsfsp,用于在 Stata 中拟合空间随机前沿模型。在过去几十年里,随机前沿模型通过纳入各种类型的空间成分取得了重要的理论进展。在效率和生产率分析中,已经开发出了能够考虑空间依赖性和溢出效应的模型,引起了工业界和学术界的广泛关注。由于缺乏统计软件包,新的随机前沿模型的经验应用显得滞后。xtsfsp命令提供了一个拟合空间随机前沿模型的程序,与Orea和Álvarez(2019,《计量经济学杂志》213:556-577)和Galli(2023,《空间经济分析》18:239-258)的风格一致,使用户能够处理不同的空间依赖性来源。在本文中,我们将介绍空间随机前沿模型,描述新命令的语法和选项,并举例说明其用法。