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Multiple Imputation Of Missing Data In Sustainable Development Modelling

Author

Listed:
  • Roberto Benedetti

    (Universita' degli Studi "G. D'Annunzio")

  • Rita Lima

    (Universita' di Palermo, Cirmet)

  • Alessandro Pandimiglio

    (Universita' degli Studi "G. D'Annunzio" e LUISS Guido Carli)

Abstract

A multiple imputation technique is proposed to measure sustainable development using models of structural equations (LISREL) for the treatment of missing data. The reliability of such technique is verified comparing the estimation model with missing data to the estimation model with imputed data. The results show that the missing data problem significantly affect the estimation.

Suggested Citation

  • Roberto Benedetti & Rita Lima & Alessandro Pandimiglio, 2006. "Multiple Imputation Of Missing Data In Sustainable Development Modelling," Economia, Societa', e Istituzioni, Dipartimento di Economia e Finanza, LUISS Guido Carli, vol. 0(3).
    • Handle: RePEc:lui:rivesi:1835
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    More about this item

    Keywords

    LISREL; Markov Chain Monte Carlo; Multiple Imputation; Sustainable Development;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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