{"title":"重要证据?有缺失数据的贫困估算","authors":"Jean Drèze, A. Somanchi","doi":"10.1177/23210222241238846","DOIUrl":null,"url":null,"abstract":"Attempts have been made to estimate poverty in India using a biased dataset, by adjusting household weights to remove or reduce the bias. The effectiveness of this method, however, is uncertain. Simulation exercises suggest that its ability to correct poverty estimates varies wildly depending on the nature of the underlying bias, which may be hard to guess—there lies the rub. When the bias changes over time, estimating poverty trends becomes truly problematic. There are wider lessons for poverty estimation with biased or missing data. JEL Codes: C83, I32","PeriodicalId":37410,"journal":{"name":"Studies in Microeconomics","volume":"92 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Weighty Evidence? Poverty Estimation with Missing Data\",\"authors\":\"Jean Drèze, A. Somanchi\",\"doi\":\"10.1177/23210222241238846\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Attempts have been made to estimate poverty in India using a biased dataset, by adjusting household weights to remove or reduce the bias. The effectiveness of this method, however, is uncertain. Simulation exercises suggest that its ability to correct poverty estimates varies wildly depending on the nature of the underlying bias, which may be hard to guess—there lies the rub. When the bias changes over time, estimating poverty trends becomes truly problematic. There are wider lessons for poverty estimation with biased or missing data. JEL Codes: C83, I32\",\"PeriodicalId\":37410,\"journal\":{\"name\":\"Studies in Microeconomics\",\"volume\":\"92 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Studies in Microeconomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/23210222241238846\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in Microeconomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/23210222241238846","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
Weighty Evidence? Poverty Estimation with Missing Data
Attempts have been made to estimate poverty in India using a biased dataset, by adjusting household weights to remove or reduce the bias. The effectiveness of this method, however, is uncertain. Simulation exercises suggest that its ability to correct poverty estimates varies wildly depending on the nature of the underlying bias, which may be hard to guess—there lies the rub. When the bias changes over time, estimating poverty trends becomes truly problematic. There are wider lessons for poverty estimation with biased or missing data. JEL Codes: C83, I32
Studies in MicroeconomicsEconomics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
1.40
自引率
0.00%
发文量
14
期刊介绍:
Studies in Microeconomics seeks high quality theoretical as well as applied (or empirical) research in all areas of microeconomics (broadly defined to include other avenues of decision science such as psychology, political science and organizational behavior). In particular, we encourage submissions in new areas of Microeconomics such as in the fields of Experimental economics and Behavioral Economics. All manuscripts will be subjected to a peer-review process. The intended audience of the journal are professional economists and young researchers with an interest and expertise in microeconomics and above. In addition to full-length articles MIC is interested in publishing and promoting shorter refereed articles (letters and notes) that are pertinent to the specialist in the field of Microeconomics (broadly defined). MIC will periodically publish special issues with themes of particular interest, including articles solicited from leading scholars as well as authoritative survey articles and meta-analysis on the themed topic. We will also publish book reviews related to microeconomics, and MIC encourages publishing articles from policy practitioners dealing with microeconomic issues that have policy relevance under the section Policy Analysis and Debate.