Abstract
ABSTRACT We provide a Bayesian spatial Markov Chain Monte Carlo model composition (MC3) analysis of growth rates in European regional patenting activity. Based on theoretical models on innovation and growth, we identify a large set of candidate explanatory variables that characterize regional stocks of knowledge, including: human resources devoted to innovative activity, scientific and technical capabilities, public and private investments, government policies, as well as regional industry structure, and indicators of regional technology gaps that reflect distance from the technological frontier. Our analysis shows that accommodating spatial dependence and heterogeneity leads to different conclusions regarding factors important for technological transfer and knowledge spillovers.
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