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The Attractiveness Of The European South As Described By A Cusp And A Butterfly Catastrophe Model

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  • VASILIS ANGELIS
  • ATHANASIOS ANGELIS-DIMAKIS
  • KATERINA DIMAKI
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    Abstract

    Over the past years a large number of regional growth theories have been developed and a number of models have been built in an effort to describe, explain and eventually predict regional development trends. However, until a few years ago, the large majority of those models assumed the existence of linear and thus regular, growth processes. Linear models are certainly able to generate unstable solutions, but the solutions of such models are restricted to certain regular standard types. Such models may provide approximate replications of short and medium, run changes, but they fail to interpret long-term developments characterized by structural shifts of an irregular nature. Furthermore, the study of regional growth through linear models is limited because it does not allow us to take into account a number of behavioural changes, opinion formation as well as economies and diseconomies of scale which are strongly characterized by non-linearities. This limitation has recently been overcome with the adoption of non-linear models which allow for a change in a system?s dynamics generated by even small perturbations in structural forms. Structural instability entails the possible existence of significant qualitative changes in the behaviour of the system (i.e. in the state variables) closely connected with bifurcation and catastrophic phenomena that may occur if the parameter values (i.e. the control variable) reach critical values. The application of non-linear models has shown that the deterministic and well-behaved unique results achieved by the dynamic linear models are no longer guaranteed: interregional convergence determined by the traditional models collapses and opens the way to alternative possible trajectories and multiple equilibria. The non-linear models are thus able to simulate an endogenous series of complex phenomena which in the past could only be replicated by means of exogenous shocks introduced ad hoc. The present paper introduces a country?s Image, a variable which expresses a country?s state of development and its future prospects. Furthermore, the factors affecting this variable are defined and ways of measuring them are suggested. Finally, these factors are grouped into different ways leading to two alternative non-linear models for the generation of country?s image. The two models are applied to the case of the European South and the values of the two sets of Images for those countries are compared and discussed. Keywords: Country?s Image, Regional Development, Sustainable Development, Economic Factors, Social Factors, Environmental Factors, Cusp Catastrophe Model, Butterfly Catastrophe Model.

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    Bibliographic Info

    Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa13p768.

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    Date of creation: Nov 2013
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    Handle: RePEc:wiw:wiwrsa:ersa13p768

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    1. Dou, Wenyu & Ghose, Sanjoy, 2006. "A dynamic nonlinear model of online retail competition using Cusp Catastrophe Theory," Journal of Business Research, Elsevier, vol. 59(7), pages 838-848, July.
    2. Vasilis Angelis & Katerina Dimaki, 2011. "A Region's Basic Image as a Measure of its Attractiveness," International Journal of Economic Sciences and Applied Research (IJESAR), Technological Educational Institute (TEI) of Kavala, Greece, vol. 4(2), pages 7-33, August.
    3. Elizabeth Karol & Julie Brunner, 2009. "Tools for Measuring Progress towards Sustainable Neighborhood Environments," Sustainability, MDPI, Open Access Journal, vol. 1(3), pages 612-627, September.
    4. Vasilis Angelis & Athanasios Angelis-Dimakis & Katerina Dimaki, 2013. "A Country's Process of Development as Described by a Butterfly Catastrophe Model: The Case of European South," International Journal of Economic Sciences and Applied Research (IJESAR), Technological Educational Institute (TEI) of Kavala, Greece, vol. 6(2), pages 25-45, September.
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