Giedre Dzemydaite (p)

Stuart McIntyre

The aim of this paper is to analyze the current trends, important for the regional economic development, and to develop and implement a theoretical concept for increasing the efficiency of regional economic development and to improve an assessment of the economic efficiency, taking into account sustainable development challenges in the context of the globalization and the EU integration.
In this paper regional economic development factors are systematized to the overall regional economic development theoretical model. The model involves quantitative and qualitative factors, back-links and integrates the concept of economic efficiency, which was supposed not to be previously included in similar models. The developed model gives a possibility to explore and assess the regional economic development trends in a broader perspective, to identify regional deficiencies, and to pay attention to the qualitative factors that are important for regional development planning and financing processes.
The research methodology integrated multivariate data analysis methods and mathematical programming techniques to better reveal regional issues. Regions of the EU member states that joined in 2004 was selected for analysis, as having common experience in the EU, the distribution of cohesion funds, market development and cultural background. Non-parametric anaysis methods, based on data envelopment analysis, were applied for the evaluation of an efficient frontier on the basis of assessing the general regional decision making units’ ability to absorb the available resources and to generate a high value-added. In this research a combination of Kohonen’s artificial neural maps with Sammon’s projection was also applied to get more information from multidimensional regional data than it was possible from the application of nonparametric techniques, to visualize the results and to get insights about regional processes and similarities between different economic indicators.
This research supports the idea that higher rate of resources does not necessarily create greater economic results and this leads to some inefficiencies in part of the regions. A higher intensity of innovative activities and R&D investments do not necessary reflects higher levels of economic performance and the logical pathway toward a higher added value is much more complex than the linear model of research: the innovation patterns are differentiated among regions according to their regional context conditions.

Daniela Bond-Smith, Steven Bond-Smith (p)

Stuart McIntyre

While the importance of human capital to innovation is widely acknowledged, human capital also indirectly affects the productivity of other innovation factors. This paper extends endogenous growth theory to include indirect human capital effects on the productivity of knowledge inputs to innovation and uses an estimator that endogenously determines the optimal sample split based on European data between 1999 and 2012. The estimator controls for the direct impact of human capital and is consistent for cross-sectional dependence. The estimation results imply that regions with human capital stocks above the 19th percentile for Europe have sufficient human capital for high innovation productivity, with consequences for the economic viability of R&D in regions below this threshold.

Vicente Rios (p), Lisa Gianmoena

Stuart McIntyre

This paper analyzes the evolution of CO2 emissions per capita in a sample of 141 countries during the period 1970-2014. The study develops a spatially augmented Green Solow Model by taking into account technological externalities and interdependence in the production process, which ultimately implies that CO2 emissions in an economy are affected by the economic characteristics in neighboring countries. The Spatial Green Solow model predicts that convergence in CO2 emissions among countries, a feature that is examined by means of dynamic spatial panel econometric techniques. Our empirical estimates suggest the existence of a convergence process, which is partly due to the role played by spatial spillovers induced by neighboring economies. In a second step, we investigate the possible existence of club convergence by means of a spatial panel data model with parameter heterogeneity and the Local Directional Moran Scatterplot. Our analysis reveals that the hypothesis of spatial convergence clubs is more consistent with the data than the hypothesis of conditional convergence. Finally, we analyze the effects of the Paris 2015 targets in the dynamic distribution of CO2 emissions.