{"title":"Assessing changes in wealth index using primary survey data","authors":"Sandeep Kumar , S. Chakraverty , Narayan Sethi","doi":"10.1016/j.seps.2024.102115","DOIUrl":null,"url":null,"abstract":"<div><div>In this study, we have introduced a new method to develop the Wealth Index (WI). In this regard, primary survey data, along with secondary data obtained from the National Family Health Survey-4 (NFHS-4) and NFHS-5 datasets, is used to construct the WI for the Koraput district in the Indian state of Odisha. Furthermore, we compared the WI obtained from the primary data with the WI obtained from the NFHS-4 and NFHS-5 data sets for Koraput and Odisha. Furthermore, to analyze wealth disparities at a finer scale, we computed and compared sub-indices in a similar manner to the WI. To develop the WI, we adopted a novel approach based on principal component analysis (PCA) with orthogonal rotation of factors whose eigenvalue is greater than 1 to utilize the maximum variance of data. The results derived from the WI and its sub-indices indicate that, when contrasted with Odisha as a whole, Koraput exhibits a lower level of wealth. The findings also reveal that, over time, there has been some improvement in wealth conditions, but they remain a cause for serious concern. Overall, the WI for the said district presents critical results, underscoring the urgent need for government or NGO intervention.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"98 ","pages":"Article 102115"},"PeriodicalIF":6.2000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Socio-economic Planning Sciences","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S003801212400315X","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we have introduced a new method to develop the Wealth Index (WI). In this regard, primary survey data, along with secondary data obtained from the National Family Health Survey-4 (NFHS-4) and NFHS-5 datasets, is used to construct the WI for the Koraput district in the Indian state of Odisha. Furthermore, we compared the WI obtained from the primary data with the WI obtained from the NFHS-4 and NFHS-5 data sets for Koraput and Odisha. Furthermore, to analyze wealth disparities at a finer scale, we computed and compared sub-indices in a similar manner to the WI. To develop the WI, we adopted a novel approach based on principal component analysis (PCA) with orthogonal rotation of factors whose eigenvalue is greater than 1 to utilize the maximum variance of data. The results derived from the WI and its sub-indices indicate that, when contrasted with Odisha as a whole, Koraput exhibits a lower level of wealth. The findings also reveal that, over time, there has been some improvement in wealth conditions, but they remain a cause for serious concern. Overall, the WI for the said district presents critical results, underscoring the urgent need for government or NGO intervention.
期刊介绍:
Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry.
Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution.
Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.