Normalizations and Misspecification in Skill Formation Models.

An important class of structural models studies the determinants of skill formation and the optimal timing of interventions. In this article, I provide new identification results for these models and investigate the effects of seemingly innocuous scale and location restrictions on parameters of inte...

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Publicado en:Review of Economic Studies Vol. 93; no. 4; pp. 2574 - 2605
Autor principal: Freyberger, Joachim
Formato: Artículo
Publicado: Oxford University Press / USA Jul2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2026
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      pub: Oxford University Press / USA
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        atl: Normalizations and Misspecification in Skill Formation Models.
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        au: Freyberger, Joachim
        affil: University of Bonn, Germany
      su:
        Economic models
        Learning
        Production functions (Economic theory)
        Parameter estimation
      sug:
        subj:
          Economic models
          Learning
          Production functions (Economic theory)
          Parameter estimation
      keyword:
        copyrightHolder:Review of Economic Studies Ltd
        copyrightYear:2026
        Factor models
        Identification
        inLanguage:en
        Measurement error
        Misspecification
        Normalizations
        publisher:Oxford University Press
        sameAs:https://dx.doi.org/10.1093/restud/rdaf078
        Skill formation
        copyrightHolder:Review of Economic Studies Ltd
        copyrightYear:2026
        Factor models
        Identification
        inLanguage:en
        Measurement error
        Misspecification
        Normalizations
        publisher:Oxford University Press
        sameAs:https://dx.doi.org/10.1093/restud/rdaf078
        Skill formation
      ab: An important class of structural models studies the determinants of skill formation and the optimal timing of interventions. In this article, I provide new identification results for these models and investigate the effects of seemingly innocuous scale and location restrictions on parameters of interest. To do so, I first characterize the identified set of all parameters without these additional restrictions and show that important policy-relevant parameters are point identified under weaker assumptions than commonly used in the literature. The implications of imposing standard scale and location restrictions depend on how the model is specified, but they generally impact the interpretation of parameters and may affect counterfactuals. Importantly, with the popular constant elasticity of substitution (CES) production function, commonly used scale restrictions fix identified parameters and lead to misspecification. Consequently, simply changing the units of measurements of observed variables might yield ineffective investment strategies and misleading policy recommendations. I show how existing estimators can easily be adapted to solve these issues. As a byproduct, this article also presents a general and formal definition of when restrictions are truly normalizations.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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