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The Determinants of Resilience in European Regions During the Great Recession: a Bayesian Model Averaging Approach

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  • Lisa Gianmoena
  • Vicente Rios
Abstract
This study analyzes the determinants of resilience outcomes of European regions during the 2008-2013 crisis. Bayesian Model Averaging techniques are used in order to examine the empirical relevance of a large number of institutional, innovation, socio-demographic and labor market factors that could affect resilience patterns. The findings of this study suggest that regional disparities in resilience patterns are mainly determined by factors such as regional quality of government, the level of innovation, the functional specialization and by national level labor market institutions. The findings are robust to (i) the definition of the dependent variable and the (ii) employment of different g-priors and priors on model size.

Suggested Citation

  • Lisa Gianmoena & Vicente Rios, 2018. "The Determinants of Resilience in European Regions During the Great Recession: a Bayesian Model Averaging Approach," Discussion Papers 2018/235, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    • Handle: RePEc:pie:dsedps:2018/235
    Note: ISSN 2039-1854
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    File URL: https://www.ec.unipi.it/documents/Ricerca/papers/2018-235.pdf
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    JEL classification:

    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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