PLoS ONE · 2020 · 11 citations · 59 references
Life SciencesEconomicsGeneticsBehavioral EconomicsCausal InferenceStatistical GeneticsCausal Inference In GeneticsDemographic AnalysisHeritabilityIncome DistributionMendelian RandomizationSelection BiasCausal Effect IdentificationCausal HypothesesCausal MarkersCognitive SkillsInstrumental Variables EstimationInstrumental Variables SpecificationNon-cognitive SkillsRisk Preference Modeling
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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