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Regional development assessment using parametric and non-parametric ranking methods: A comparative analysis of Slovenia and Croatia

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  • Dario Cziraky
  • Jaksa Puljiz
  • Joze Rovan
  • Joze Sambt
  • Mario Polic
  • Sanja Malekovic

Abstract

In this paper we describe several regional development-assessment methods and subsequently apply them in a comparative development level analysis of the Slovenian and Croatian municipalities. The aim is to compare performance and suitability of several parametric and non-parametric ranking methods and to develop a suitable multivariate methodological framework for distinguishing development level of particular territorial units. However, the usefulness and appropriateness of various multivariate techniques for regional development assessment is generally questionable and there is no clear consensus about how to carry out such analysis. Two main methodological approaches are based on parametric and non-parametric methods, where in the former an explicit econometric model containing theory-implied causal and possibly simultaneous relationships is estimated using likelihood-based methods and formally assessed in terms of the goodness of fit and other test statistics, subsequently allowing for estimation of the development level on a metric scale, while in the later, territorial units or regions are essentially classified into clusters or groups differing in the development level, but no formal inferential methods are applied to confirm the validity of the model, or to establish the difference in the development level on a metric scale. The possible advantages of the first approach are in the existence of formal testing and evaluation procedures, as well as in producing interval ranks of the analysed units, while its disadvantages are in the lack of robustness; often unrealistic distributional assumptions; and possible invalidity of the theoretically implied causal relationships. In this paper we consider a parametric, inferential approach based on maximum likelihood estimation of the linear structural equation model with latent variables for metric-scale development ranking, and a non-parametric approach based on cluster analysis for development grouping. Our analysis is based on ten regional development variables such as income per capita, population density, age index, etc. which are similarly collected and generally compatible for both analysed countries. Within the parametric approach, a simultaneous equation econometric model is estimated and latent scores are computed for each underlying latent development variable, where three latent constructs are postulated corresponding to economic, structural and demographic development dimensions. In the non-parametric approach, a combination of Ward?s hierarchical method and K-means clustering procedure is applied to classify the territorial units. We apply both methodological frameworks to Slovenian and Croatian municipality data and assess their regional development level. We further compare the performance of both methods and show to which degree their results are compatible. Finally, we propose a unified framework based on both parametric and non-parametric methods, where clustering techniques are performed both on the original development indicators and on the computed latent scores from the structural equation model, and compare these results with the results from each of the two methods applied separately. We show that a combined parametric/non-parametric approach is superior to each approach applied individually and propose a methodological framework capable of estimating the development level of territorial units or regions on a metric scale, while in the same time preserving the robustness of the non-parametric techniques.

Suggested Citation

  • 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.
  • Handle: RePEc:wiw:wiwrsa:ersa03p350
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    References listed on IDEAS

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    1. Soares, Joao Oliveira & Marques, Maria Manuela Lourenco & Monteiro, Carlos Manuel Ferreira, 2003. "A multivariate methodology to uncover regional disparities: A contribution to improve European Union and governmental decisions," European Journal of Operational Research, Elsevier, vol. 145(1), pages 121-135, February.
    2. Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
    3. 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.
    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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    1. Senetra, Adam & Szarek-Iwaniuk, Patrycja, 2019. "The implementation of the Wroclaw taxonomic method for the identification and evaluation of problem areas in the Warmia and Mazury Region in Poland – A case study," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 43-57.
    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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