ALTERNATIVE FUNCTIONAL FORMS AND ERRORS OF PSEUDO DATA ESTIMATION.

The article presents some results from a pseudo data analysis of a small hypothetical process model that casts doubt about the usefulness of the approach. In the article, the authors discusses the statistical properties of the errors, the question of the appropriate norm for approximation errors; th...

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Publicado en:Review of Economics & Statistics Vol. 62; no. 2; pp. 323 - 328
Autores principales: Maddala, G.S., Roberts, R. Blaine
Formato: Artículo
Publicado: MIT Press May80
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: ALTERNATIVE FUNCTIONAL FORMS AND ERRORS OF PSEUDO DATA ESTIMATION.
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          Maddala, G.S.
          Roberts, R. Blaine
      su:
        Economic forecasting
        Error analysis in mathematics
        Elasticity (Economics)
        Prices
        Diversification in industry
        Labor
        Model validation
        Quantitative research
        Cost estimates
      sug:
        subj:
          Economic forecasting
          Error analysis in mathematics
          Elasticity (Economics)
          Prices
          Diversification in industry
          Labor
          Model validation
          Quantitative research
          Cost estimates
      ab: The article presents some results from a pseudo data analysis of a small hypothetical process model that casts doubt about the usefulness of the approach. In the article, the authors discusses the statistical properties of the errors, the question of the appropriate norm for approximation errors; the alternative functional forms; and the issue of single versus multiple equation methods of estimation. An illustrative analysis of a small process model and the resulting elasticities are presented. The purpose of the "pseudo data approach" is to condense the technical information in a complex process analysis model into a single equation. This single equation summarization is supposed to give estimates of several price and substitution elasticities as well as input-output coefficients which can presumably be used in other modeling exercises. The authors states that their examples illustrates the fact that the elasticity estimates obtained from the single equation summarization of the data generated from the process model are likely to be unstable and thus, not of much use.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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