Best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in US counties
{"title":"Best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in US counties","authors":"Fei Jin, Lung-fei Lee, Kai Yang","doi":"10.1002/jae.3046","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>We provide a novel analytic procedure to construct best linear and quadratic moments of the generalized method of moments estimation for a large class of cross-sectional network and spatial econometric models. These moments generate an estimator that is asymptotically more efficient than the quasi-maximum likelihood estimator when the disturbances follow a non-normal and unknown distribution. We apply this procedure to a high-order spatial autoregressive model with spatial errors, where the disturbances are heteroskedastic. Two normality tests of disturbances are developed. We apply the model to employment data in US counties, which demonstrates spatial interdependence patterns of regional employment growth.</p>\n </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 4","pages":"640-658"},"PeriodicalIF":2.3000,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Econometrics","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jae.3046","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
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Abstract
We provide a novel analytic procedure to construct best linear and quadratic moments of the generalized method of moments estimation for a large class of cross-sectional network and spatial econometric models. These moments generate an estimator that is asymptotically more efficient than the quasi-maximum likelihood estimator when the disturbances follow a non-normal and unknown distribution. We apply this procedure to a high-order spatial autoregressive model with spatial errors, where the disturbances are heteroskedastic. Two normality tests of disturbances are developed. We apply the model to employment data in US counties, which demonstrates spatial interdependence patterns of regional employment growth.
期刊介绍：
The Journal of Applied Econometrics is an international journal published bi-monthly, plus 1 additional issue (total 7 issues). It aims to publish articles of high quality dealing with the application of existing as well as new econometric techniques to a wide variety of problems in economics and related subjects, covering topics in measurement, estimation, testing, forecasting, and policy analysis. The emphasis is on the careful and rigorous application of econometric techniques and the appropriate interpretation of the results. The economic content of the articles is stressed. A special feature of the Journal is its emphasis on the replicability of results by other researchers. To achieve this aim, authors are expected to make available a complete set of the data used as well as any specialised computer programs employed through a readily accessible medium, preferably in a machine-readable form. The use of microcomputers in applied research and transferability of data is emphasised. The Journal also features occasional sections of short papers re-evaluating previously published papers. The intention of the Journal of Applied Econometrics is to provide an outlet for innovative, quantitative research in economics which cuts across areas of specialisation, involves transferable techniques, and is easily replicable by other researchers. Contributions that introduce statistical methods that are applicable to a variety of economic problems are actively encouraged. The Journal also aims to publish review and survey articles that make recent developments in the field of theoretical and applied econometrics more readily accessible to applied economists in general.
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