Occupations, Human Capital and Skills.

Economists have long recognized that occupations can be used as proxies for skills in wage regressions. Yet the potential existence of non-market factors such as discrimination and occupational choice (sorting) on the basis of job attributes that are separate from, but potentially correlated with, w...

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Publicado en:Journal of Labor Research Vol. 31; no. 4; pp. 365 - 387
Autores principales: Levenson, Alec, Zoghi, Cindy
Formato: Artículo
Publicado: Springer Science & Business Media B.V. December 2010
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Acceso en línea:Ver este registro en EBSCOhost
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      dt: December 2010
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      pub: Springer Science & Business Media B.V.
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        10.1007/s12122-010-9098-x
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          Levenson, Alec
          Zoghi, Cindy
      su:
        Job classification
        Wage differentials
        Employment & education
        Skilled labor
        Human capital
        Mathematical models
        Wages
        United States
      sug:
        subj:
          United States
          Job classification
          Wage differentials
          Employment & education
          Skilled labor
          Human capital
          Mathematical models
          Wages
      ab: Economists have long recognized that occupations can be used as proxies for skills in wage regressions. Yet the potential existence of non-market factors such as discrimination and occupational choice (sorting) on the basis of job attributes that are separate from, but potentially correlated with, wages makes occupations an imperfect control for skills. In this paper, we consider whether inter-occupational wage differentials that are unexplained by measured human capital are indeed due to differences in unmeasured skill. Using the National Compensation Survey, a large, nationally-representative dataset on jobs and ten different components of job requirements, we compare the effects on residual wage variation of including occupation indicators and these skill requirements measures. We find that although these skill requirements vary across 3-digit occupations, occupation indicators decrease wage residuals by far more than can be explained by skill alone. This indicates that “controlling for occupation” does not equate to controlling for only these skill measures, but also for other factors. Additionally, we find that there is considerable within-occupation variation in skill requirements, and that the amount of variation is not constant across skill levels. As a result, including occupation indicators in a wage model introduces heteroskedasticity that must be accounted for. We suggest that caution be applied when using and interpreting occupation indicators as controls in wage regressions. Reprinted by permission of the publisher.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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