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Developing a composite index by using spatial latent modelling based on information theoretic estimation


  • Rosa Bernardini Papalia


  • Enrico Ciavolino



The focus of this paper is on spatial structural equation models (S-SEM) also extended to a Panel data framework. More specifically, our objective is to introduce a generalized maximum entropy formulation for the class of S-SEM with the aim of developing a composite index. We present an application of the method to real data finalized to investigate dynamics and complex interactions between some selected dimensions that represent the main measures of intangible assets for a panel of OECD countries over the period 1998–2008. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Rosa Bernardini Papalia & Enrico Ciavolino, 2015. "Developing a composite index by using spatial latent modelling based on information theoretic estimation," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 989-997, May.
  • Handle: RePEc:spr:qualqt:v:49:y:2015:i:3:p:989-997
    DOI: 10.1007/s11135-014-0159-8

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    References listed on IDEAS

    1. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    2. R. Bernardini Papalia, 2008. "A Composite Generalized Cross-Entropy Formulation in Small Samples Estimation," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 596-609.
    3. Rosa Bernardini Papalia & Enrico Ciavolino, 2011. "GME Estimation of Spatial Structural Equations Models," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 126-141, April.
    4. repec:taf:gnstxx:v:21:y:2009:i:8:p:1017-1036 is not listed on IDEAS
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