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Covariance structure analysis of regional development data: an application to municipality development assessment

Author

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  • Jurlin, Kresimir

  • Malekovic, Sanja

  • Puljiz, Jaksa

  • Cziraky, Dario

  • Polic, Mario

Abstract

This paper presents the results of the second phase of the project whose main objective is to provide an analytical basis for evaluating the level of development of the Croatian territorial units, i.e. municipalities in this particular case. In the second phase, a structural equation model with latent variables is estimated with the purpose to test the validity of the first (simple) model and its results. The structural model takes into account complex casual relations between simple and joint indicators (factors) used in the model, but its output is a single development level scale which allows interval ranking of the territorial units. On the other hand, the first model makes distinctions between municipalities according to each collective indicator (economic, structural and demogeographic), but it assumes that collective indicators are independent. As the intention from the beginning of the project was to try to categorise territorial units according to the methodology used by Structural Funds and based on NUTS classification, the first model was used for the final evaluation and categorisation of the territorial units, but it was somewhat changed according to the results of the structural equation model.

Suggested Citation

  • Jurlin, Kresimir & Malekovic, Sanja & Puljiz, Jaksa & Cziraky, Dario & Polic, Mario, 2002. "Covariance structure analysis of regional development data: an application to municipality development assessment," ERSA conference papers ersa02p469, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa02p469
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    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa02/cd-rom/papers/469.pdf
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    References listed on IDEAS

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    1. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    2. Gerbing, David W & Anderson, James C, 1984. "On the Meaning of Within-Factor Correlated Measurement Errors," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(1), pages 572-580, June.
    3. Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
    4. Gabriel Lipshitz & Adi Raveh, 1998. "Socio-economic Differences among Localities: A New Method of Multivariate Analysis," Regional Studies, Taylor & Francis Journals, vol. 32(8), pages 747-757.
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    Cited by:

    1. Dario Cziraky & Jaksa Puljiz & Joze Rovan & Joze Sambt & Mario Polic & Sanja Malekovic, 2003. "Regional development assessment using parametric and non-parametric ranking methods: A comparative analysis of Slovenia and Croatia," ERSA conference papers ersa03p350, European Regional Science Association.
    2. Cziraky, Dario & Sambt, Joze & Rovan, Joze & Puljiz, Jaksa, 2006. "Regional development assessment: A structural equation approach," European Journal of Operational Research, Elsevier, vol. 174(1), pages 427-442, October.

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