{"title":"有限种群中的推断和外推,特别注意聚类","authors":"R. Startz, D. Steigerwald","doi":"10.1080/07474938.2023.2178137","DOIUrl":null,"url":null,"abstract":"Abstract Statistical inference in economics is commonly based on formulas assuming infinite populations. We present appropriate formulas for use when sampling from finite populations, with special attention given to issues of treatment effects and to issues of clustering. Issues of whether to apply finite population corrections are often subtle, and appropriate corrections may depend on difficult to observe parameters, leaving the investigator only with bounds on relevant estimator variances.","PeriodicalId":11438,"journal":{"name":"Econometric Reviews","volume":"42 1","pages":"343 - 357"},"PeriodicalIF":0.8000,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inference and extrapolation in finite populations with special attention to clustering\",\"authors\":\"R. Startz, D. Steigerwald\",\"doi\":\"10.1080/07474938.2023.2178137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Statistical inference in economics is commonly based on formulas assuming infinite populations. We present appropriate formulas for use when sampling from finite populations, with special attention given to issues of treatment effects and to issues of clustering. Issues of whether to apply finite population corrections are often subtle, and appropriate corrections may depend on difficult to observe parameters, leaving the investigator only with bounds on relevant estimator variances.\",\"PeriodicalId\":11438,\"journal\":{\"name\":\"Econometric Reviews\",\"volume\":\"42 1\",\"pages\":\"343 - 357\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Reviews\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1080/07474938.2023.2178137\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Reviews","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/07474938.2023.2178137","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
Inference and extrapolation in finite populations with special attention to clustering
Abstract Statistical inference in economics is commonly based on formulas assuming infinite populations. We present appropriate formulas for use when sampling from finite populations, with special attention given to issues of treatment effects and to issues of clustering. Issues of whether to apply finite population corrections are often subtle, and appropriate corrections may depend on difficult to observe parameters, leaving the investigator only with bounds on relevant estimator variances.
期刊介绍:
Econometric Reviews is widely regarded as one of the top 5 core journals in econometrics. It probes the limits of econometric knowledge, featuring regular, state-of-the-art single blind refereed articles and book reviews. ER has been consistently the leader and innovator in its acclaimed retrospective and critical surveys and interchanges on current or developing topics. Special issues of the journal are developed by a world-renowned editorial board. These bring together leading experts from econometrics and beyond. Reviews of books and software are also within the scope of the journal. Its content is expressly intended to reach beyond econometrics and advanced empirical economics, to statistics and other social sciences.