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      What is creating the height premium? New evidence from a Mendelian randomization analysis in China

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          Abstract

          This study uses a Mendelian randomization approach to resolve the difficulties of identifying the causal relationship between height and earnings by using a unique sample of 3,427 respondents from mainland China with sociodemographic information linked to individual genotyping data. Exploiting genetic variations to create instrumental variables for observed height, we find that while OLS regressions yield that an additional centimeter in height is associated with a 10–13% increase in one’s annual earnings, IV estimates reveal only an insubstantial causal effect of height. Further analyses suggest that the observed height premium is likely to pick up the impacts of several cognitive/noncognitive skills on earnings confounded in previous studies, such as mental health, risk preference, and personality factors. Our study is the first empirical study that employs genetic IVs in developing countries, and our results contribute to the recent debate on the mechanism of height premium.

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          Most cited references40

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          Identification of Causal Effects Using Instrumental Variables

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            Global Evidence on Economic Preferences*

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              The Role of Premarket Factors in Black-White Wage Differences

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                Author and article information

                Contributors
                Role: ConceptualizationRole: ResourcesRole: Validation
                Role: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Methodology
                Role: Data curationRole: Methodology
                Role: Data curation
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 April 2020
                2020
                : 15
                : 4
                : e0230555
                Affiliations
                [1 ] School of Public Administration and Policy, Renmin University of China, Beijing, China
                [2 ] Center for Health Policy Research and Evaluation, Renmin University of China, Beijing, China
                [3 ] College of Economics and Management, China Agricultural University, Beijing, China
                [4 ] WeGene, Shenzhen, China
                University of Jyvaskyla, FINLAND
                Author notes

                Competing Interests: Gang Chen and Yingxiang Li are employees of WeGene. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0003-3582-9022
                Article
                PONE-D-19-31929
                10.1371/journal.pone.0230555
                7147798
                32275720
                d02bf379-6b76-4e3f-b883-c69b315f8b9a
                © 2020 Wang et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 November 2019
                : 2 March 2020
                Page count
                Figures: 3, Tables: 7, Pages: 20
                Funding
                The authors received no specific funding for this work. WeGene provided data support of collecting and analyzing genotyping data, but did not have any additional role in financially supporting the current study.
                Categories
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                Labor Economics
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                Custom metadata
                Data cannot be shared publicly because of the Regulation on the Administration of Human Genetic Resources (effective since July 1, 2019) promulgated by China's State Council. Data are available from the WeGene Research Team (contact via Dr. Lizhong Wang<wanglz@ 123456wegene.com >) for researchers who meet the criteria for access to confidential data.

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