{"title":"估算学校教育回报的能力代用指标的有效性:基于因子模型的评估","authors":"Mohitosh Kejriwal, Xiaoxiao Li, Linh Nguyen, Evan Totty","doi":"10.1002/jae.3011","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>A common approach to addressing ability bias is to augment the earnings-schooling regression with proxies for cognitive and non-cognitive skills. We evaluate this approach using a factor model framework, which allows consistent estimation of the returns to schooling without relying on proxies. The factor model estimators may be viewed as implicitly estimating proxy measurement error and/or accounting for omitted dimensions of ability. A bias decomposition quantifies the contribution of the proxies while the estimated latent skills are used to construct direct tests for their viability. Both sets of results confirm the inadequacy of the proxies in capturing the latent skills.</p>\n </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The efficacy of ability proxies for estimating the returns to schooling: A factor model-based evaluation\",\"authors\":\"Mohitosh Kejriwal, Xiaoxiao Li, Linh Nguyen, Evan Totty\",\"doi\":\"10.1002/jae.3011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>A common approach to addressing ability bias is to augment the earnings-schooling regression with proxies for cognitive and non-cognitive skills. We evaluate this approach using a factor model framework, which allows consistent estimation of the returns to schooling without relying on proxies. The factor model estimators may be viewed as implicitly estimating proxy measurement error and/or accounting for omitted dimensions of ability. A bias decomposition quantifies the contribution of the proxies while the estimated latent skills are used to construct direct tests for their viability. Both sets of results confirm the inadequacy of the proxies in capturing the latent skills.</p>\\n </div>\",\"PeriodicalId\":48363,\"journal\":{\"name\":\"Journal of Applied Econometrics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Econometrics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jae.3011\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Econometrics","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jae.3011","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
The efficacy of ability proxies for estimating the returns to schooling: A factor model-based evaluation
A common approach to addressing ability bias is to augment the earnings-schooling regression with proxies for cognitive and non-cognitive skills. We evaluate this approach using a factor model framework, which allows consistent estimation of the returns to schooling without relying on proxies. The factor model estimators may be viewed as implicitly estimating proxy measurement error and/or accounting for omitted dimensions of ability. A bias decomposition quantifies the contribution of the proxies while the estimated latent skills are used to construct direct tests for their viability. Both sets of results confirm the inadequacy of the proxies in capturing the latent skills.
期刊介绍:
The Journal of Applied Econometrics is an international journal published bi-monthly, plus 1 additional issue (total 7 issues). It aims to publish articles of high quality dealing with the application of existing as well as new econometric techniques to a wide variety of problems in economics and related subjects, covering topics in measurement, estimation, testing, forecasting, and policy analysis. The emphasis is on the careful and rigorous application of econometric techniques and the appropriate interpretation of the results. The economic content of the articles is stressed. A special feature of the Journal is its emphasis on the replicability of results by other researchers. To achieve this aim, authors are expected to make available a complete set of the data used as well as any specialised computer programs employed through a readily accessible medium, preferably in a machine-readable form. The use of microcomputers in applied research and transferability of data is emphasised. The Journal also features occasional sections of short papers re-evaluating previously published papers. The intention of the Journal of Applied Econometrics is to provide an outlet for innovative, quantitative research in economics which cuts across areas of specialisation, involves transferable techniques, and is easily replicable by other researchers. Contributions that introduce statistical methods that are applicable to a variety of economic problems are actively encouraged. The Journal also aims to publish review and survey articles that make recent developments in the field of theoretical and applied econometrics more readily accessible to applied economists in general.