Diana Gutiérrez Posada (p), Tania Fernández García, André Carrascal Incera

Garri Raagmaa

Innovation increases productivity, and in turn competitiveness and wealth; the problem is the trade-off between the traditional economic objectives/dynamics linked to it (via agglomeration economies) and the reduction of inequalities, which rises the question: is it possible to tackle spatial inequality through innovation? Innovation generates growth, but that growth is unevenly distributed in space. This suggests a positive association between innovation and regional inequality overall. However, when looking at the regional level, there are some European regions that seem to be catching up in the grounds of investment in R&D. Is indeed R&D nurturing growth in those regions or are there other confounding effects? Can those examples be extrapolated to other regions in Europe? What policy practices could be implemented to reconciliate innovation and regional convergence? Given the existence of the spatial heterogeneity already mentioned, the question is whether a single estimate can properly explain this regional phenomenon. Spatial non-stationarity takes place when the responses to particular variables change across space, and these differences might be caused by the interrelationships between neighboring regions. Adopting a global regression approach might lead to deceptive estimates if those are extrapolated to the local environment. In view of this limitation, the methodological approach adopted in this analysis will be that of Geographically Weighted Regressions (GWR), which will allow us to observe the different response inequality has to different depictions of innovative effort/performance across the European territory.

Andre Carrascal-Incera (p), Tania Fernández García , Carmen Ramos Carvajal

Diana Gutiérrez Posada

This paper follows the framework developed in Los (2001) where the author presents a model combining the characteristics of endogenous growth modelling and Input-Output analysis. By means of a dynamic input-output model, Los (2001) takes into account important characteristics of endogenous growth models such as innovation and knowledge spillovers, but accounting for macroeconomic balance conditions at the same time. This paper aims to understand and estimate the possible short and long-term effects of an increase in R&D investment in the productivity of a region and its growth path. We perform the analysis for 17 Spanish regions using information from two different sources: first, the ones related to the Input-Output structure of the regions, mainly the EUREGIO and additional information from official regional Input-Output databases; and second, the Spanish National Statistical Office (INE) for the data on R&D investment by region and sector.

Tania Fernández García (p), Fernando Rubiera Morollón

Andre Carrascal-Incera

Advance technology has been created to satisfy the needs of developed territories; they have the resources, and specifically the human capital highly qualified to use new technologies efficiently in contrast to less developed ones (Samuelson and Nordhaus, 2010). In fact, recent empirical evidence showed that lagging or peripheral regions are those less benefited from investing in Research and Development (R&D) since they have a lower capacity to innovate (Filippopoulos and Fotopoulos, 2021; Marques and Morgan, 2021; Rodríguez-Pose, Wilkie and Zhang, 2021). In this sense, there seemed to be a consensus among neoclassical economist: differences in terms of human capital are the main drivers of the technological gaps between territories (Nelson and Phelps, 1966; Romer, 1990). The fundamental objective of this work is to analyze if European peripheral regions need to complement increases in R&D expenditures with increases in the amount of highly qualified individuals to experiment significant and relevant effects on their economic growth rates. For mentioned purpose a growth model is developed for the context of the European regions (NUTS2) following a β-convergence equation considering the period 2008-2019. In addition to include variables related to region´s R&D expenditure, level of education, income per capita, employment rate or population density, we include a key variable: an interaction term between regions R&D expenditure and their level of education. Thanks to this term we will explore if there is a necessary condition for peripheral regions to complement education policies, aiming to improve their educational systems, with innovation policies, aiming to increase R&D expenditures, or vice versa. The selected methodology is Geographically Weighted Regression (GWR). Specifically, this technique consists in a local analysis permitting us to estimate a set of parameters for each spatial unit. Results confirm that European peripheral regions need to accompany R&D expenditures with other policies oriented to increase their level of education. However, most developed regions, mainly those that belong to the Nordic countries, benefit from marginal increases in the educational level or from punctual investments in R&D. There are two important implications. First, invest in R&D is not a unique recipe for boosting the economic growth of every region. Second, policies should be adapted to territories own socioeconomic characteristics. Specifically, we consider that the accumulation of human capital could be placed as an instrument that could favor the efficient use of the invested resources in R&D in peripheral regions of Europe.

Garri Raagmaa (p)

Tania Fernández García

This paper analyses peripheral regions in the framework of a knowledge economy and one of its infrastructural elements – regional higher education institutions (RHEI). The paper contributes to the rural innovation and smart specialisation debate by arguing that to be successful regional higher education institutions must act not only as educators but also as proactive institutional entrepreneurs, shaping regional strategies and institutional development. On the other hand, national innovation policies shall consider and systematically improve regional R&D and innovation capacity.
The paper provides a theoretical background about the potential role of regional higher educational institutions in peripheral locations, gives some examples from the Nordic countries. The empirical part describes shortly the Estonian RHEIs based on the earlier Estonian Science and Innovation Policy Evaluation report sub-study and reflects the main findings from the recent evaluation reports.
It concludes that the EU structural funds supported innovation policies have been rather increasing regional differences. The outputs and impact of the policy measures are not clearly and logically interlinked as they are initiated from different ministerial silos. The existing potential of RHEIs has been modestly utilised and the successful rural restructuring, introduction of new industries and bottom-up discoveries as the key to the smart specialisation depends mainly on local leadership and agency.