{"title":"Panel Time Series","authors":"Ron P. Smith, Ana‐Maria Fuertes","doi":"10.1002/9781119504641.ch8","DOIUrl":null,"url":null,"abstract":"Traditionally economic panels had large number of cross-section units and relatively few time periods and econometric methods were developed for such large N small T data. More recently panels with observations for a large numbers of time periods have become available on cross-section units like \u0085rms, industries, regions or countries. These notes explore the econometric methods developed for such large N large T data. Such data allow more explicit treatment of (a) heterogeneity across units (b) dynamics, including the treatment of unit roots and cointegration and (c) cross-section dependence arising from spatial interactions or unobserved common factors.","PeriodicalId":273652,"journal":{"name":"Panel Data Econometrics with R","volume":"246 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Panel Data Econometrics with R","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/9781119504641.ch8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
Traditionally economic panels had large number of cross-section units and relatively few time periods and econometric methods were developed for such large N small T data. More recently panels with observations for a large numbers of time periods have become available on cross-section units like rms, industries, regions or countries. These notes explore the econometric methods developed for such large N large T data. Such data allow more explicit treatment of (a) heterogeneity across units (b) dynamics, including the treatment of unit roots and cointegration and (c) cross-section dependence arising from spatial interactions or unobserved common factors.