{"title":"年龄堆积模式与数据质量:来自1991-2016年印度住户调查数据的证据","authors":"M. Malik","doi":"10.1080/23737484.2021.1952492","DOIUrl":null,"url":null,"abstract":"Abstract Age structure is crucial to various socio-economic and demographic factors. Better age quality data are critical to determine the reliability of large scale household surveys and the estimates they provide. Considering the importance and large sample these household surveys represent, we examined one of India’s largest household survey (NFHS) to determine its data quality and accuracy. Using multiple indices we also made a comparison of various age reporting measures to assess pattern of age heaping. Our results found that age heaping is a gray concern for household surveys in India. Though there has been some improvement, but over all age quality data are still very rough, affecting likely the survey estimates. Females are performing better on contrary to what earlier studies have found, which is likely due to improving socio-cultural and living norms in Indian settings. It is clear that age preference can likely cause the substantial biases in demographic factors and survey estimates. Thus studies examining age structure or any such methods where age is significantly important should adjust the age bias before carrying out further analysis. Furthermore, a single approach for age adjustment techniques is must to improve the age quality data for better policy implications.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"11 1","pages":"382 - 393"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Age heaping pattern and data quality: evidence from Indian Household Survey Data (1991–2016)\",\"authors\":\"M. Malik\",\"doi\":\"10.1080/23737484.2021.1952492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Age structure is crucial to various socio-economic and demographic factors. Better age quality data are critical to determine the reliability of large scale household surveys and the estimates they provide. Considering the importance and large sample these household surveys represent, we examined one of India’s largest household survey (NFHS) to determine its data quality and accuracy. Using multiple indices we also made a comparison of various age reporting measures to assess pattern of age heaping. Our results found that age heaping is a gray concern for household surveys in India. Though there has been some improvement, but over all age quality data are still very rough, affecting likely the survey estimates. Females are performing better on contrary to what earlier studies have found, which is likely due to improving socio-cultural and living norms in Indian settings. It is clear that age preference can likely cause the substantial biases in demographic factors and survey estimates. Thus studies examining age structure or any such methods where age is significantly important should adjust the age bias before carrying out further analysis. Furthermore, a single approach for age adjustment techniques is must to improve the age quality data for better policy implications.\",\"PeriodicalId\":36561,\"journal\":{\"name\":\"Communications in Statistics Case Studies Data Analysis and Applications\",\"volume\":\"11 1\",\"pages\":\"382 - 393\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications in Statistics Case Studies Data Analysis and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23737484.2021.1952492\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Statistics Case Studies Data Analysis and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23737484.2021.1952492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Mathematics","Score":null,"Total":0}
Age heaping pattern and data quality: evidence from Indian Household Survey Data (1991–2016)
Abstract Age structure is crucial to various socio-economic and demographic factors. Better age quality data are critical to determine the reliability of large scale household surveys and the estimates they provide. Considering the importance and large sample these household surveys represent, we examined one of India’s largest household survey (NFHS) to determine its data quality and accuracy. Using multiple indices we also made a comparison of various age reporting measures to assess pattern of age heaping. Our results found that age heaping is a gray concern for household surveys in India. Though there has been some improvement, but over all age quality data are still very rough, affecting likely the survey estimates. Females are performing better on contrary to what earlier studies have found, which is likely due to improving socio-cultural and living norms in Indian settings. It is clear that age preference can likely cause the substantial biases in demographic factors and survey estimates. Thus studies examining age structure or any such methods where age is significantly important should adjust the age bias before carrying out further analysis. Furthermore, a single approach for age adjustment techniques is must to improve the age quality data for better policy implications.