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Multiple Imputation Of Missing Data In Sustainable Development Modelling

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Author Info
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.

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File URL: http://www.luiss.it/RePEc/pdf/esi1835.pdf
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Publisher Info
Article provided by Department of Economic and Business Sciences, LUISS Guido Carli in its journal Economia, Societa', e Istituzioni.

Volume (Year): XVIII (2006)
Issue (Month): 3 ()
Pages:
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Handle: RePEc:lui:rivesi:1835

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Related research
Keywords: LISREL; Markov Chain Monte Carlo; Multiple Imputation; Sustainable Development;

Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
O10 - Economic Development, Technological Change, and Growth - - Economic Development - - - General

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