Fitting spatial autoregressive logit and probit models using Stata: The spatbinary command

IF 3.2 2区 数学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS Stata Journal Pub Date : 2022-06-01 DOI:10.1177/1536867X221106373
Daniele Spinelli
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Abstract

Starting from version 15, Stata allows users to manage data and fit regressions accounting for spatial relationships through the sp commands. Spatial regressions can be estimated using the spregress, spxtregress, and spivregress commands. These commands allow users to fit spatial autoregressive models in cross-sectional and panel data. However, they are designed to estimate regressions with continuous dependent variables. Although binary spatial regressions are important in applied econometrics, they cannot be estimated in Stata. Therefore, I introduce spatbinary, a Stata command that allows users to fit spatial logit and probit models.
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使用Stata拟合空间自回归logit和probit模型:spatbinary命令
从版本15开始,Stata允许用户通过sp命令管理数据和拟合空间关系的回归。空间回归可以使用spregress、spxtreress和spivregress命令来估计。这些命令允许用户在横断面和面板数据中拟合空间自回归模型。然而,它们被设计用来估计具有连续因变量的回归。虽然二元空间回归在应用计量经济学中很重要,但在Stata中无法估计。因此,我介绍了一个Stata命令,它允许用户拟合空间logit和probit模型。
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来源期刊
Stata Journal
Stata Journal 数学-统计学与概率论
CiteScore
7.80
自引率
4.20%
发文量
44
审稿时长
>12 weeks
期刊介绍: The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.
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