{"title":"从分组数据计算回归统计","authors":"Jörg Schwiebert","doi":"10.3233/JEM-150416","DOIUrl":null,"url":null,"abstract":"This paper considers regression techniques for grouped data. In particular, it is shown how regression statistics obtained from individual level data can be replicated by means of grouped data. Three common regression approaches are considered: ordinary least squares, instrumental variables and nonlinear least squares regression. Also provided is code to implement the grouped-data techniques in the econometric software package Stata. An empirical example illustrates that the grouped-data formulas indeed replicate the statistics obtained from the individual level data. It is also argued why grouped data are important for empirical research.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"39 1","pages":"283-303"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-150416","citationCount":"1","resultStr":"{\"title\":\"Computing regression statistics from grouped data\",\"authors\":\"Jörg Schwiebert\",\"doi\":\"10.3233/JEM-150416\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers regression techniques for grouped data. In particular, it is shown how regression statistics obtained from individual level data can be replicated by means of grouped data. Three common regression approaches are considered: ordinary least squares, instrumental variables and nonlinear least squares regression. Also provided is code to implement the grouped-data techniques in the econometric software package Stata. An empirical example illustrates that the grouped-data formulas indeed replicate the statistics obtained from the individual level data. It is also argued why grouped data are important for empirical research.\",\"PeriodicalId\":53705,\"journal\":{\"name\":\"Journal of Economic and Social Measurement\",\"volume\":\"39 1\",\"pages\":\"283-303\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.3233/JEM-150416\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Economic and Social Measurement\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/JEM-150416\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic and Social Measurement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JEM-150416","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
This paper considers regression techniques for grouped data. In particular, it is shown how regression statistics obtained from individual level data can be replicated by means of grouped data. Three common regression approaches are considered: ordinary least squares, instrumental variables and nonlinear least squares regression. Also provided is code to implement the grouped-data techniques in the econometric software package Stata. An empirical example illustrates that the grouped-data formulas indeed replicate the statistics obtained from the individual level data. It is also argued why grouped data are important for empirical research.
期刊介绍:
The Journal of Economic and Social Measurement (JESM) is a quarterly journal that is concerned with the investigation of all aspects of production, distribution and use of economic and other societal statistical data, and with the use of computers in that context. JESM publishes articles that consider the statistical methodology of economic and social science measurements. It is concerned with the methods and problems of data distribution, including the design and implementation of data base systems and, more generally, computer software and hardware for distributing and accessing statistical data files. Its focus on computer software also includes the valuation of algorithms and their implementation, assessing the degree to which particular algorithms may yield more or less accurate computed results. It addresses the technical and even legal problems of the collection and use of data, legislation and administrative actions affecting government produced or distributed data files, and similar topics. The journal serves as a forum for the exchange of information and views between data producers and users. In addition, it considers the various uses to which statistical data may be put, particularly to the degree that these uses illustrate or affect the properties of the data. The data considered in JESM are usually economic or social, as mentioned, but this is not a requirement; the editorial policies of JESM do not place a priori restrictions upon the data that might be considered within individual articles. Furthermore, there are no limitations concerning the source of the data.