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      Height and cognition at work: Labor market productivity in a low income setting

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      Economics & Human Biology
      Elsevier BV

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          Abstract

          <p class="first" id="P1">Taller workers earn more, particularly in lower income settings. It has been argued that adult height is a marker of strength which is rewarded in the labor market; a proxy for cognitive performance or other dimensions of human capital such as school quality; a proxy for health status; and a proxy for family background and genetic characteristics. As a result, the argument goes, height is rewarded in the labor market because it is an informative signal of worker quality to an employer. It has also been argued that the height premium is driven by occupational and sectoral choice. This paper evaluates the relative importance of these potential mechanisms underlying the link between adult stature and labor market productivity in a specific low income setting, rural Central Java, Indonesia. Drawing on twelve waves of longitudinal survey data, we establish that height predicts hourly earnings after controlling education, multiple indicators of cognitive performance and physical health status, measures of family background, sectoral and occupational choice, as well as local area market characteristics. The height premium is large and significant in both the wage and self-employed sectors indicating height is not only a signal of worker quality to employers. Since adult stature is largely determined in the first few years of life, we conclude that exposures during this critical period have an enduring impact on labor market productivity. </p>

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          Author and article information

          Journal
          Economics & Human Biology
          Economics & Human Biology
          Elsevier BV
          1570677X
          May 2017
          May 2017
          : 25
          : 52-64
          Article
          10.1016/j.ehb.2016.10.008
          5419881
          27843117
          f01818ca-5b5d-4513-ae2a-0cb8afbf8c74
          © 2017

          https://www.elsevier.com/tdm/userlicense/1.0/

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