{"title":"教育不匹配的收入惩罚:评估过度教育的不同方法的比较","authors":"Le Wen, S. Maani","doi":"10.1080/00779954.2022.2034175","DOIUrl":null,"url":null,"abstract":"In this paper we systematically evaluate the impact of using the alternative methods conventionally used in the international literature on the measured incidence of educational mismatch and its earnings effects. We use a rich Australian longitudinal data set for a controlled group of full-time employed workers. Using panel data estimation, we address individual heterogeneity and measurement error, which are important in educational mismatch analysis. We show that alternative methods of measurement result in a range of estimates, with the Mode measure providing the most stable results across instrumental variables (IV) selections in panel fixed effects instrumental variables (FEIV) estimations. Based on the Mode measure, the incidence rate of over-education is 32.3%. The earnings penalty for each year of over-education is 2.5%, which is larger than 0.6% in fixed effect estimation and also larger than 1.9% in OLS estimations.","PeriodicalId":38921,"journal":{"name":"New Zealand Economic Papers","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Earnings penalty of educational mismatch: a comparison of alternative methods of assessing over-education\",\"authors\":\"Le Wen, S. Maani\",\"doi\":\"10.1080/00779954.2022.2034175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we systematically evaluate the impact of using the alternative methods conventionally used in the international literature on the measured incidence of educational mismatch and its earnings effects. We use a rich Australian longitudinal data set for a controlled group of full-time employed workers. Using panel data estimation, we address individual heterogeneity and measurement error, which are important in educational mismatch analysis. We show that alternative methods of measurement result in a range of estimates, with the Mode measure providing the most stable results across instrumental variables (IV) selections in panel fixed effects instrumental variables (FEIV) estimations. Based on the Mode measure, the incidence rate of over-education is 32.3%. The earnings penalty for each year of over-education is 2.5%, which is larger than 0.6% in fixed effect estimation and also larger than 1.9% in OLS estimations.\",\"PeriodicalId\":38921,\"journal\":{\"name\":\"New Zealand Economic Papers\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-02-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"New Zealand Economic Papers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/00779954.2022.2034175\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Zealand Economic Papers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00779954.2022.2034175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
Earnings penalty of educational mismatch: a comparison of alternative methods of assessing over-education
In this paper we systematically evaluate the impact of using the alternative methods conventionally used in the international literature on the measured incidence of educational mismatch and its earnings effects. We use a rich Australian longitudinal data set for a controlled group of full-time employed workers. Using panel data estimation, we address individual heterogeneity and measurement error, which are important in educational mismatch analysis. We show that alternative methods of measurement result in a range of estimates, with the Mode measure providing the most stable results across instrumental variables (IV) selections in panel fixed effects instrumental variables (FEIV) estimations. Based on the Mode measure, the incidence rate of over-education is 32.3%. The earnings penalty for each year of over-education is 2.5%, which is larger than 0.6% in fixed effect estimation and also larger than 1.9% in OLS estimations.