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Spatially Augmented Analysis of Macroeconomic Convergence with Application to the Czech Republic and Its Neighbors

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Applied Computational Intelligence and Mathematical Methods (CoMeSySo 2017)

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Abstract

This paper deals with macroeconomic convergence at the NUTS2 level for the following six countries: Czechia, Slovakia, Poland, Hungary, Germany and Austria. Prominent spatial dependencies are identified and compared to the Solow-Swan type convergence. The estimation and testing is performed using spatial panel data methodology. At the theoretical and empirical level, properties and performance of spatial panel models are compared with classical cross-sectional and panel (non-spatial) approaches. Given the variety of available frameworks of modeling and estimation of spatial dependencies, significant proportion of this paper is devoted to model specification and robustness analysis issues. Also, topics relevant for appropriate interpretation of the estimated spatio-temporal models are included.

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Acknowledgement

Supported by the grant No. IGA F4/58/2017, Faculty of Informatics and Statistics, University of Economics, Prague. Geo-data source: GISCO - Eurostat (European Commission), Administrative boundaries: © EuroGeographics.

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Correspondence to Tomáš Formánek .

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Formánek, T. (2018). Spatially Augmented Analysis of Macroeconomic Convergence with Application to the Czech Republic and Its Neighbors. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Applied Computational Intelligence and Mathematical Methods. CoMeSySo 2017. Advances in Intelligent Systems and Computing, vol 662. Springer, Cham. https://doi.org/10.1007/978-3-319-67621-0_1

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  • DOI: https://doi.org/10.1007/978-3-319-67621-0_1

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