Abstract
New entrepreneurial ventures may represent a viable and effective mechanism to transform academic knowledge into regional economic growth. We test this notion for the Italian provinces between 2001 and 2006. We evaluate three outputs of academic activities: teaching, research and intellectual property rights activities. New ventures may be able to transform the mentioned outputs into improved economic performance. The findings show that the effects of academic outputs on provincial economic growth (all sectors) are appreciable when they are associated with sustained entrepreneurial activities in the province. It suggests that academic inquiry may provide new ventures with valuable commercial opportunities overseen by established companies.
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Notes
University involvement in a region is not by definition a guarantee for success. University initiatives may for example tend to follow instead of cause vibrant high-technology clusters. Breznitz (2011) describes how constant one-sided changes in technology transfer policy and organization have had a negative effect on Cambridge University’s ability to commercialize technology.
Adams (1990) shows that between 1949 and 1983 it took around 20 years for scientific advancements to be absorbed and exploited by industries and ultimately lead to productivity growth.
See Carree and Thurik (2003) for a review of the renewed economic interest in entrepreneurship.
High entry rates can also force incumbents to explore new sources of knowledge, including academic knowledge, and to make a better use of it. We thank an anonymous referee for raising this point.
Two arguments to defend our decision to focus on administrative provinces can be provided. First, by specifically addressing the issue of spatial autocorrelation, we are able to explain to what extent the neighbouring provinces might have an effect on growth in the focal province, therefore providing an indirect measure of the reasonableness of the use of this administrative spatial cluster as unit of analysis. Second, Italian provinces include the capital city of the corresponding administrative region and these capitals are usually relatively large cities with the surrounding towns closely connected to that city for economic, social, cultural, and spatial reasons. As recently shown in a study performed for the European Commission (Europe Innova 2010), the largest concentrations of entrepreneurial activities with favorable perspectives of growth in Europe are major urban areas, which attract the most talented workers.
In 2001, the existing provinces of Sardinia (4 provinces) were reorganized in 8 new provinces. For this reason, we have excluded the provinces located in the region. Hence, we are left with 99 provinces which represent the remaining 19 Italian regions in 2001. There are 75 universities in 47 out of 99 provinces. Note that the number or provinces has increased in the last decade. As of 2004, there are already 110 provinces.
Although we cannot a priori exclude that entry of entrepreneurial ventures may also stimulate incumbent firms to take advantage of the academic knowledge-base in the province.
Table 1 presents a concise description of the variables employed and the source.
The measures of entry are concurrent with the measures of growth. The reason is that entry of new capacities has direct effects on growth in the same year (Fritsch and Mueller, 2008). Possible reverse causation (growth leading to entry) should be limited given that it takes time to set up a new venture.
We follow the sectors aggregation used by EUROSTAT. Although four classifications are proposed—high, medium high, medium–low and low tech—we grouped the first two in high-tech and the remaining two in low-tech.
To construct our variable Publications, we retrieved from the website of ISI, for any given province in any given year, the number of articles in Science and Technology disciplines containing the capital cities of the Italian provinces in the addresses of the authors’ affiliations. The outcome was then refined to include all possible spellings of the universities in the province and exclude other organizations. The final refined outcome was the number of articles published by scientists located in a given province in a given year. Hence, articles published by scientists of different universities located in the same province where counted only once, whereas the same article published by scientists in different provinces was counted as many times as the provinces—but only once per province.
The inclusion of a lagged dependent variable in a fixed effects model may give rise to biases, especially for the effect of the lagged dependent variable. However, since the dependent variable is a change and we are not interested in the coefficient for the lagged dependent variables, the biases should be minimal. See also Bun and Carree (2005).
Quatraro (2009) discusses the process of structural change that occurred in Italian regions between 1980 and 2000. The author documents a process of de-industrialization in the early-industrialized Northwest regions with consequent transformation to a knowledge-based economy, and an increasing specialization in manufacturing activities in the Northeast and Central regions focused on traditional sectors. Furthermore the author shows that a process of recent industrialization is occurring in the developing South.
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Acknowledgments
We thank David Audretsch, Erik Lehmann, Mike Wright, Roberta Piergiovanni, and two anonymous referees for helpful suggestions. E. Santarelli acknowledges financial support from University of Bologna (RFO2009 and RFO2010). A. Della Malva acknowledges financial support from European Commission under the program COST-STRIKE (COST-STSM-IS0604-5332).
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Carree, M., Malva, A.D. & Santarelli, E. The contribution of universities to growth: empirical evidence for Italy. J Technol Transf 39, 393–414 (2014). https://doi.org/10.1007/s10961-012-9282-7
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DOI: https://doi.org/10.1007/s10961-012-9282-7