Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: Taller individuals typically have occupations with higher social status and higher earnings than shorter individuals. Further, entrepreneurship is associated with high social status in numerous countries; hence, entrepreneurs might be taller than wage workers. Using data from the German Socio-Economic Panel (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010), we find that a 1 cm increase in an individual's height raises the probability of being self-employed (the most common proxy for entrepreneurship) versus paid employed by 0.16 percentage-points. Within self-employment the probability of being an employer is increased by 0.11 percentage-points as a result of a 1 cm increase in height whereas this increase is 0.05 percentage-points for an own-account worker. Furthermore, we confirm that a height premium in earnings exists for not only paid employees, as indicated by prior studies, but also for self-employed individuals. An additional 1 cm in height is associated with a 0.44% increase in hourly earnings for paid employees, and a 0.87% increase for self-employed individuals. The predicted earnings differences between short and tall individuals are substantial. Short paid employees-first quartile of height-earn 15.5 Euros per hour whereas tall paid employees-third quartile of height-earn 16.5 Euros per hour; in self-employment the earnings are 12.8 and 14.4 Euros per hour, respectively. Another novel finding is that we establish the existence of a height premium for work and life satisfaction, but only for paid employees. Finally, our analysis reveals that 44% of the height premium in earnings is explained by differences in educational attainment whereas the height premium in work and life satisfaction is only marginally explained by education. Terms of use: Documents in
Nature (one's genes) and nurture (one's environment) jointly contribute to the formation and evolution of health and human capital over the life cycle. This complex interplay between genes and environment can be estimated and quantified using genetic information readily available in a growing number of social science data sets. To help the novice reader interested in understanding individual decision making, public policy, and inequality using genetic data, we introduce essential genetic terminology, review the literature in economics and social-science genetics---with a focus on the interplay between genes and environment---and discuss policy implications and future prospects of the use of genetic data in the social sciences and economics.
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