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

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Abstract

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.

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Notes

  1. Other spatial model specifications with lagged terms for all dimensions are also used to check the robustness of the Lag- Model including only the spatial innovation component.

  2. Sweden, Finland, Denmark, Norway, Iceland, Netherlands, Belgium, Switzerland, United Kingdom, Germany, Ireland, France, Austria, Spain, Slovenia, Greece, Italy, Portugal, Hungary, Poland, Czech Republic, Estonia, Lithuania, Latvia, Turkey, Bulgaria, Romania.

  3. Source: World Bank, OECD, USPTO.

  4. Source: UNESCO, World Bank.

  5. Source: World values Survey.

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Authors and Affiliations

  1. Department of Statistics, University of Bologna, Via Belle Arti n. 41, 40100, Bologna, Italy

    Rosa Bernardini Papalia

  2. Department of History, Society and Human Studies, University of Salento Palazzo Parlangeli, Via V.M.Stampacchia n. 45, 73100, Lecce, Italy

    Enrico Ciavolino

Authors
  1. Rosa Bernardini Papalia
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  2. Enrico Ciavolino
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Correspondence to Rosa Bernardini Papalia.

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Bernardini Papalia, R., Ciavolino, E. Developing a composite index by using spatial latent modelling based on information theoretic estimation. Qual Quant 49, 989–997 (2015). https://doi.org/10.1007/s11135-014-0159-8

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  • DOI: https://doi.org/10.1007/s11135-014-0159-8

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