{"title":"The Spatial Autoregressive Panel Data Model with Spatial Moving Average Errors","authors":"Chang Tan, J. Paul Elhorst","doi":"10.1111/gean.12369","DOIUrl":null,"url":null,"abstract":"<p>This paper advocates the wider use of the spatial autoregressive (AR) panel data model with spatial moving average (MA) errors, individual and time effects, and different spatial weight matrices for each spatial lag. We demonstrate the practical relevance of this model, derive and investigate the asymptotic properties of a simple quasi maximum likelihood within estimator when <math>\n <semantics>\n <mrow>\n <mi>N</mi>\n </mrow>\n <annotation>$$ N $$</annotation>\n </semantics></math> is large and <math>\n <semantics>\n <mrow>\n <mi>T</mi>\n </mrow>\n <annotation>$$ T $$</annotation>\n </semantics></math> is finite, and provide an empirical example explaining military expenditures in 144 countries over the period 1993–2007.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"56 1","pages":"40-61"},"PeriodicalIF":3.3000,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.12369","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geographical Analysis","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/gean.12369","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0
Abstract
This paper advocates the wider use of the spatial autoregressive (AR) panel data model with spatial moving average (MA) errors, individual and time effects, and different spatial weight matrices for each spatial lag. We demonstrate the practical relevance of this model, derive and investigate the asymptotic properties of a simple quasi maximum likelihood within estimator when is large and is finite, and provide an empirical example explaining military expenditures in 144 countries over the period 1993–2007.
本文提倡更广泛地使用空间自回归（AR）面板数据模型，该模型具有空间移动平均（MA）误差、个体和时间效应以及每个空间滞后的不同空间权重矩阵。我们证明了这一模型的实用性，推导并研究了当 N $$ N $$ 较大且 T $$ T $$ 有限时，一个简单的准最大似然估计器的渐近特性，并提供了一个解释 144 个国家 1993-2007 年军事支出的实证例子。
期刊介绍：
First in its specialty area and one of the most frequently cited publications in geography, Geographical Analysis has, since 1969, presented significant advances in geographical theory, model building, and quantitative methods to geographers and scholars in a wide spectrum of related fields. Traditionally, mathematical and nonmathematical articulations of geographical theory, and statements and discussions of the analytic paradigm are published in the journal. Spatial data analyses and spatial econometrics and statistics are strongly represented.
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