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Innovation, entrepreneurial activity and competitiveness at a sub-national level

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Abstract

The capability to generate new knowledge and to create new firms differs across regions. Our study is an attempt to test the extent to which differences in such capabilities are associated with regional competitiveness. Using data from Spanish NUTS2 regions for the period 2000–2004, our results show that a higher capacity of a region to simultaneously generate new knowledge and start-up firms is positively linked to its level of competitiveness. This finding supports the belief that innovation per se is a necessary, but not sufficient, condition for regional economic development.

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Notes

  1. The Romer (1986) model is an extension of the neo-classical model in which knowledge, R it , is added as an input and, more specifically, is considered an endogenous element of technological change, in addition to human capital (Romer 1990).

  2. Zahra et al. (2006) analyse in detail the concept of “dynamic capability”, distinguishing between the knowledge base at a given time (substantive capacities), the potential to increase this knowledge base over time (dynamic capabilities), and the result (economic growth). We shall define dynamic capabilities and regional economic growth as the following notations, respectively: \( ^{{}} Ln\left( {{\frac{{A_{t + 1} }}{{A_{t} }}}} \right);_{{}}^{{}} Ln\left( {{\frac{{Y_{t + 1} }}{{Y_{t} }}}} \right). \)

  3. We leave for further research the study of the endogenous process of this virtual cycle between economic development and innovation.

  4. Apart from academic studies, some of the principal contributions to the analysis of entrepreneurial activity and economic development in countries and regions have come from reports published by the GEM project over the past few years. Such results also show that entrepreneurial activity in less developed countries correlates negatively with per capita income and that, on achieving a certain welfare level, a threshold is reached after which the relation becomes positive for the more developed countries.

  5. For instance, empirical evidence suggests that entrepreneurs with high-growth aspirations and those committed to global markets are more likely to contribute to economic growth than other entrepreneurs (Hessels and van Stel 2009; Wong et al. 2005).

  6. See http://www.ine.es for more information.

  7. Net capital stock is a common measure of capital contribution to growth even though productive capital is the most appropriate measure. However, the latter is not published at an aggregated level for each region. Accordingly, in order to use a more proper measure of capital, the value of housing was subtracted from the net capital stock value because it is not directly involved in production and may reflect speculative activities.

  8. Similarly, the scree test (Cattel 1996), based on examining the graph of eigenvalues and looking for the natural break point from which the curve flattens out, suggests retaining two factors.

  9. These dummy variables are embedded in the productivity term A jt , except for that representing the reference category.

  10. For example Catalonia has top international Business Schools such as ESADE (http://www.esade.edu) and IESE (http://www.iese.edu) and a Engineering School with a wide academic offer (UPC, http://www.upc.edu).

  11. Inter-region migration is measured as the residential variation using data from INE.

  12. Although innovation and entrepreneurial capabilities are considered under the heading S j , there are other relevant regional not observed characteristics (i.e. sector distribution, degree of competition, foreign investment, etc.) that are associated with economic growth or productivity. The case of Madrid is a clear example, it concentrates all the relevant public institutions (national such as ministries and international such as embassies), it is increasingly specialized in financial services (most of the Spanish commercial banks have moved their central offices to Madrid) and jointly with Catalonia has the most well-renowned Spanish universities. In econometric terms, both random and fixed effects deal with those not observed characteristics. The Hausman (1978) test is the accepted tool to determine whether the estimator of fixed effects may be higher than the estimator of random effects. In particular, the null hypothesis of the Hausman test is that the difference between the parameters is not systematic, in other words that the information contained in the random and fixed estimates is no different statistically. In the three models presented in the “Results” section regional fixed effects outperform random effects. For example, in Model 3 the statistical test for our model is 83.79 (P = 0.0000) with five degrees of freedom. Besides, the increase of R 2 in the models is close to 40% when fixed effects are included. The results displayed in Table 3 therefore contain the dummy variables of each region (here, Autonomous Community).

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Acknowledgments

The authors are sincerely grateful to the comments received from two anonymous referees, Juan José Gibaja, Erik Lehman, Pedro Ortín and Scott Shane on previous versions of the paper. All errors, interpretations and omissions are the authors’ responsibility. Ferran Vendrell-Herrero acknowledges the financial support received from the Spanish Ministry of Education and Science (Project SEJ 2007-67895-C04-04). José L. González-Pernía and Iñaki Peña-Legazkue acknowledge the financial support received from the Spanish Ministry of Science and Innovation (Project ECO2009-08735).

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González-Pernía, J.L., Peña-Legazkue, I. & Vendrell-Herrero, F. Innovation, entrepreneurial activity and competitiveness at a sub-national level. Small Bus Econ 39, 561–574 (2012). https://doi.org/10.1007/s11187-011-9330-y

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