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Abstract

The authors employ a Bayesian Model Averaging (BMA) framework to study economic growth determinants of the 276 European regions during 2006-2015 period. This framework allows one to address, as much as possible to date, the model uncertainty problem. Application of BMA provides a possibility to run simultaneously numerous models to test each determinant in all possible variations. By controlling for top 500 higher education institutions over the world, the authors find statistical evidence that not only quantity of educational institutions does matter, but also the quality of each. In fact, it is one of the significant determinants of economic growth. Also, the model proves that higher education level, higher share of ICT patents, higher prime age population share, as well as higher manufacturing share are positively associated with subsequent economic growth; whereas, capital city regions tend to develop faster. The regions that tend to have a higher share of people with primary-only education have forecasted slower growth, as well as CO 2 emissions and rapid population growth tend to have a negative correlation with economic growth. The findings suggest that a high share of information and communication technologies patents and a high share of industry in gross value added (GVA) will positively affect economic development. The authors also found a positive spillover effect from the neighbouring regions. Finally, the findings confirm a conditional convergence process among European regions -regions with higher initial income tend to develop slower if other factors remain unchanged. AbstractTechnopreneurship has become a lever to propel creativity and innovation in businesses today. This study investigates the impact of technopreneurship on business performance among agro-businesses in Abeokuta, Ogun State, Nigeria. The study examined empirical evidences on the impact of technopreneurship on business performance. The survey method was adopted. The quantitative research design was employed. Yamane formula was used to determine the sample size. A sample of 126 respondents was selected through random sampling method from of a population of 183 agro-businesses within the study areas and 74% response rate was recorded. Primary method of data collection was used. A well-structured questionnaire was administered and responses were analysed using linear regression on SPSS (Statistical Package for Social Sciences) version 20. The survey demonstrates that technological innovation has significant effect on firm competitiveness (P = 0.000 < 0.05; R 2 = 0.183) and also technological opportunities significantly influence on firm operational efficiency (P = 0.000 < 0.05; R 2 = 0.445). Based on the results of findings, the study recommends that businesses need to develop or exploit indigenous technology; new products or processes based innovations; seek new technology ideas and significant technological changes which are key to competitiveness. AbstractIn the National Development Plan of Latvia 2014-2020 it is written that socie...