{"title":"单位加权均值——因为规模很重要","authors":"Eugene Canjels","doi":"10.2139/ssrn.3565305","DOIUrl":null,"url":null,"abstract":"The unit-weighted mean is of frequent interest to applied researchers in a wide range of fields. Despite this interest, there is a lack of easily accessible theoretical statistical literature that shows its statistical properties. This paper provides the asymptotic distribution of the unit-weighted mean and a formula to calculate asymptotically valid standard errors. I show that numerically identical results can be obtained using a novel regression approach.","PeriodicalId":416026,"journal":{"name":"Econometric Modeling: Corporate Finance & Governance eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Unit-Weighted Mean - Because Size Matters\",\"authors\":\"Eugene Canjels\",\"doi\":\"10.2139/ssrn.3565305\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The unit-weighted mean is of frequent interest to applied researchers in a wide range of fields. Despite this interest, there is a lack of easily accessible theoretical statistical literature that shows its statistical properties. This paper provides the asymptotic distribution of the unit-weighted mean and a formula to calculate asymptotically valid standard errors. I show that numerically identical results can be obtained using a novel regression approach.\",\"PeriodicalId\":416026,\"journal\":{\"name\":\"Econometric Modeling: Corporate Finance & Governance eJournal\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Modeling: Corporate Finance & Governance eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3565305\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Modeling: Corporate Finance & Governance eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3565305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The unit-weighted mean is of frequent interest to applied researchers in a wide range of fields. Despite this interest, there is a lack of easily accessible theoretical statistical literature that shows its statistical properties. This paper provides the asymptotic distribution of the unit-weighted mean and a formula to calculate asymptotically valid standard errors. I show that numerically identical results can be obtained using a novel regression approach.