Are Science Cities Fostering Firm Innovation?
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PRELIMINARY AND INCOMPLETE – DO NOT CITE Are Science Cities Fostering Firm Innovation? Evidence from Russia’s Regions 1 Helena Schweiger Paolo Zacchia European Bank for Reconstruction and University of California – Berkeley Development [email protected] [email protected] February 2015 Abstract: Using a mixture of data from the recent regionally representative Business Environment and Enterprise Performance Survey (BEEPS) in Russia as well as municipal level data, we find that there are significant differences in innovation activity of firms and cities across the Russian regions. We investigate whether this could be explained by the proximity to science cities – towns with a high concentration of research and development facilities, as well as human capital. They were selected and given this status in a largely random way during Soviet times. We match the science and non-science cities on their historic and geographical characteristics and compare the innovation activity (R&D, product and process innovation) of firms in science cities with the innovation activity of similar-in-the-observables firms in similar, non-science cities. Preliminary evidence suggests that firms located in science cities were more likely to engage in product and process innovation than firms located in similar, non-science cities. The results have important policy implications because many countries in the world, including developing countries, have been introducing science parks or other areas of innovation, viewing them as a type of silver bullet with the capability of dramatically improving a country’s ability to compete in the global economy and help the country to grow. JEL Classification: O33, O38, O14 Keywords: Innovation, Russia, science cities 1 We would like to thank Natalya Volchkova, Sergei Guriev and Maria Gorban for helpful discussions and Irina Capita, Jan Lukšič, Alexander Stepanov and Maria Vasilenko for excellent research assistance. The views expressed in this paper are our own and do not necessarily represent those of the institutions of affiliation. 1 Introduction There is general consensus that innovation is essential for accelerating the growth of the economy. Governments can support innovation indirectly by implementing reforms to foster innovation or directly through public investment in science and basic research (OECD 2007). The mix between the two varies by country, but over the last 50 years, it included various types of place-based policies 2 - science, technology, research, or science and technology parks, technology centres, and granting cities the status of a science city in a number of countries 3 - with the aim of promoting a culture of competitiveness and innovation of the firms located there, stimulating technological spillovers and ultimately contributing to faster economic growth. There is evidence that innovation activity is more spatially concentrated than population and economic activity (see Carlino and Kerr 2014 for an overview). Localised knowledge spillovers are often considered – along with labor market pooling and intermediate goods provision cost-type advantage – as one of the theoretical explanations for the existence of agglomeration economies, dating back at least to Marshall (1890). 4 It is important to note that, despite the fact that (localized) knowledge spillovers are most often related to agglomeration externalities, there is no reason not to assume that they are also playing a role in more limited settings especially where research is very concentrated. A challenge in identifying typically unobservable local knowledge spillovers is to disentangle them from the technological spillovers that arise between firms that are technologically close but not necessarily spatially close – particularly so because technologically similar firms tend to locate near one another. In addition, this is a natural case where the econometric “reflection” endogeneity problem (Manski 1993) kicks in – it is hard to tell ‘who spills on whom’ and whether the productivity differentials are not Just caused by common, for instance localized, shocks. Moretti (2004) hints at 2 Place –based policies, which are defined as specific government or otherwise external interventions – be it in the form of directed financial support for economic activities or investment, or in the form of special regulations – that are directed to specific, well-defined geographical areas. Such policies are typically either directed to the poorest areas in the case of the advanced economies, in order for these to catch up with the rest of the country, or to the areas that are considered to have the best potential for growth in the case of developing countries or transition economies, as it is often thought that this may at some point spur growth in surrounding areas as well as the rest of the country. 3 International Association of Science Parks and Areas of Innovation (IASP), which was established in 1984, has 398 members in 73 countries, covering all continents apart from Antarctica ( http://www.iasp.ws/facts-and- figures , 9 February 2015). Science city status has been awarded by national governments to cities in China, Germany, Japan, Philippines, Russia, Spain, Sweden, Switzerland, United Arab Emirates and UK (Wikipedia - http://en.wikipedia.org/wiki/Science_City). 4 While theories are old, careful empirical studies that quantify the sources of agglomeration economies are much more recent. An excellent example is a study by Greenstone et al. (2010), who employ a matching-like methodology that compares locations where a very large plant has opened to the locations that were very close to be chosen in their place. They find very large agglomeration productivity externalities - an effect of around 10 per cent increase - that result from the opening of a “Million Dollar Plant” (MDP), and wide heterogeneity across locations in the estimated effect. In addition, firms/plants belonging to a close technological class seem to enJoy more the opening of the MDP, hinting at a central role for knowledge exchange in generating the externalities. A notable analysis that attempts to quantify patterns of industrial co- agglomeration is Ellison et al. (2010), who are able to assess the impact of all three main theories of agglomeration economies. 2 the presence of localized knowledge spillovers by showing that productivity at the local level depends on the relative level of education of the whole workforce. Jaffe et al. (1993) and Lychagin et al. (forthcoming) address the issue with a different perspective. Using U.S. patent data, the former find that citation patterns are locally clustered. Lychagin et al. in particular attempt to separately distinguish three kinds of knowledge spillovers using US data: horizontal spillovers across product-market rivals, technology spillovers across firms that are close in the technological space, and geographical-locational spillovers. They find that in terms of correlations, geographical spillovers matter as much as technology spillovers once the latter are controlled for. However, their study is mostly descriptive, as they do not control for endogeneity of R&D; hence it does not really attack the two aforementioned endogeneity problems. The literature on the evaluation of place-based policies is to a large extent even less developed. Relatively recent examples of this category of studies are the papers by Wang (2013), Wren and Taylor (1999), Albouy (2012), Papke (1996), Busso et al. (2013), Ham et al. (2011), Neumark and Kolko (2010). Most of these are focused on the short-run. An exception is the study by Kline and Moretti (2014), who assess the long-run impact of a large-scale place-based policy enacted in the US at the times of the New Deal, namely the Tennessee Valley Authority (TVA) program. Their empirical results, even if they are consistent with the presence of agglomeration economies, do not seem to confirm the existence of strong non-linearities that would strongly motivate large place-based policies. Knowledge-focused place-based policies and their assessment have received much less attention, not only because they are far less common. Moreover, innovation and its outcomes are much harder to measure even in conventional, not geographically focused studies; in addition, slightly different analytical frameworks are needed. Empirical evidence on the performance of science parks as one available knowledge-focused place-based policy instrument is mixed. Rather than functioning as “seedbeds” of innovation, Felsenstein (1994) suggested they are closer to functioning as “enclaves” of innovation. Westhead (1997) found no statistically significant differences in R&D outputs of new technology-based firms located within and outside of the science parks in the United Kingdom. Lindelöf and Löfsten (2003) found that new technology-based firms located within science parks in Sweden placed more emphasis on innovative activities than their outside counterparts. Yang et al. (2009), on the other hand, find that new technology-based firms in a Taiwanese science park invest more efficiently in innovation than those outside of the science park. 5 In this paper we contribute to the literature by evaluating the legacy of innovation-oriented place- based policies in the former Soviet Union on firm- and municipal-level innovation in present-day Russia. The former Soviet Union was in a way a pioneer of such policies, with public investment in science and basic research approach. The model of innovation followed by the Soviet authorities