{"title":"用噪声数据衡量印度的经济流动性:部分识别方法","authors":"Hao Li, Daniel Millimet, Punarjit Roychowdhury","doi":"10.1093/jrsssa/qnac005","DOIUrl":null,"url":null,"abstract":"Abstract We examine economic mobility in India while accounting for misclassification to better understand the welfare effects of the rise in inequality. To proceed, we extend recently developed methods on the partial identification of transition matrices. Allowing for modest misclassification, we find overall mobility has been remarkably low: at least 65% of poor households remained poor or at-risk of being poor between 2005 and 2012. We also find Muslims, lower caste groups, and rural households are in a more disadvantageous position compared to Hindus, upper caste groups, and urban households. These findings cast doubt on the conventional wisdom that marginalized households in India are catching up.","PeriodicalId":49985,"journal":{"name":"Journal of the Royal Statistical Society","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Measuring economic mobility in India using noisy data: a partial identification approach\",\"authors\":\"Hao Li, Daniel Millimet, Punarjit Roychowdhury\",\"doi\":\"10.1093/jrsssa/qnac005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract We examine economic mobility in India while accounting for misclassification to better understand the welfare effects of the rise in inequality. To proceed, we extend recently developed methods on the partial identification of transition matrices. Allowing for modest misclassification, we find overall mobility has been remarkably low: at least 65% of poor households remained poor or at-risk of being poor between 2005 and 2012. We also find Muslims, lower caste groups, and rural households are in a more disadvantageous position compared to Hindus, upper caste groups, and urban households. These findings cast doubt on the conventional wisdom that marginalized households in India are catching up.\",\"PeriodicalId\":49985,\"journal\":{\"name\":\"Journal of the Royal Statistical Society\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Royal Statistical Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/jrsssa/qnac005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Royal Statistical Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jrsssa/qnac005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Measuring economic mobility in India using noisy data: a partial identification approach
Abstract We examine economic mobility in India while accounting for misclassification to better understand the welfare effects of the rise in inequality. To proceed, we extend recently developed methods on the partial identification of transition matrices. Allowing for modest misclassification, we find overall mobility has been remarkably low: at least 65% of poor households remained poor or at-risk of being poor between 2005 and 2012. We also find Muslims, lower caste groups, and rural households are in a more disadvantageous position compared to Hindus, upper caste groups, and urban households. These findings cast doubt on the conventional wisdom that marginalized households in India are catching up.