{"title":"面板时间序列","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":"{\"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}","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}
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.