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on Innovation |
| By: | Lars Mewes; Tom Broekel |
| Abstract: | Previous research shows ample evidence that regional diversification is strongly path-dependent, as regions are more likely to diversify into related than unrelated activities. In this paper, we ask whether contemporary innovation policy in form of R&D subsidies intervenes in the process of regional diversification. We focus on R&D subsidies and assess if they cement existing path-dependent developments, or if they help in breaking these by facilitating unrelated diversification. To investigate the role of R&D policy in the process of regional technological diversification, we link information on R&D subsidies with patent data and analyze the diversification of 141 German labor-market regions into new technology classes between 1991 and 2010. Our findings suggest that R&D subsidies positively influence regional technological diversification. In addition, we find significant differences between types of subsidy. Subsidized joint R&D projects have a larger effect on the entry probabilities of technologies than subsidized R&D projects conducted by single organizations. To some extent, collaborative R&D can even compensate for missing relatedness by facilitating diversification into unrelated technologies. |
| Keywords: | regional technological diversification, relatedness, innovation, policy, R&D subsidies |
| JEL: | O31 O33 O38 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2003&r=all |
| By: | Reinhold Kosfeld (University of Kassel); Timo Mitze (Southern University of Denmark) |
| Abstract: | Modern cluster theory provides reasons for positive external effects that accrue from the interaction of spatially proximate firms operating in common and related fields of economic activity. In this paper, we examine the impact of R&D-intensive clusters as a key factor of regional competitiveness on productivity and innovation growth. In analogy to the industry-oriented concepts of related and unrelated variety (Frenken, Van Oort, Verburg 2007), we differentiate between effects of cluster specialisation and diversity. The identification of R&D-intensive clusters is based on a hybrid approach of qualitative input-output analysis and spatial scanning (Kosfeld and Titze 2017). Our empirical study is conducted for a panel of German NUTS-3 regions in 2001-2011. To comprehensive account for specialisation and diversity effects of clustering we adopt a spatial econometric approach, which allows us to identify these effects beyond the geographical boundaries of a single region. After controlling for regional characteristics and unobserved heterogeneity, a robust ‘cluster strength’ effect (i.e. specialization) on productivity growth is found within the context of conditional convergence across German regions. With regard to the underlying mechanisms, we find that the presence of a limited number of R&D-intensive clusters in specific technological fields is most strongly linked to higher levels of regional productivity growth. While we also observe a positive effect of cluster strength on innovation growth once we account for spatial spillovers, no significant effects of ‘cluster diversity’ can be identified. This indicates that some but not all cluster-based regional development strategies are promising policy tools to foster regional growth processes. |
| Keywords: | Industry clusters, regional competitiveness, cluster specialisation, cluster diversity, correlated random effects model |
| JEL: | L16 R11 R15 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:mar:magkse:202001&r=all |
| By: | Pinchetti, Marco |
| Abstract: | In this paper, I incorporate a Schumpeterian mechanism of creative destruction in a medium-scale DSGE framework. In the model, a sector of profit-maximizing innovators invests in R&D and endogenously gen- erates productivity gains, ultimately determining the economy's growth rate. I estimate the model using Bayesian methods on U.S. data of the last 25 years (1993q1-2018q4) in order to disentangle the key forces underlying the productivity slowdown experienced by the US economy since the early 2000s. In contrast with the previous literature, I exploit Fernald (2014) data on TFP, factor utilization and labour quality to discipline the production function, and find that the bulk of the TFP slowdown is due to a decrease in innovation's ability to generate TFP gains. These findings challenge the view of a large part of the literature, according to which the recent TFP dynamics in the US are mostly driven by demand slumps and/or liquidity crunches. |
| Keywords: | DSGE model, Endogenous TFP, Schumpeterian Growth, TFP Slowdown |
| JEL: | E24 E32 E5 O47 |
| Date: | 2020–01–24 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:98316&r=all |
| By: | Alexander Coad; Gianluca Biggi; Elisa Giuliani |
| Abstract: | Industrial innovation churns out increasingly unnatural products and technologies amid scientific uncertainty about their harmful effects. We argue that a quick regulatory response to the discovery that certain innovations are harmful is an important indicator for evaluating the performance of an innovation system. Using a unique hand-collected dataset, we explore the temporal geography of regulatory responses as evidenced by the years in which countries introduce bans against leaded petrol, asbestos, DDT, smoking in public places, and plastic bags, as well as introducing the driver’s seatbelt obligation. We find inconsistent regulatory responses by countries across different threats, and that countries’ level of economic development is often not a good predictor of early bans. Moreover, an early introduction of one ban is not strongly related to the relative performance in regard to another ban, which raises possible questions about the coherence of regulatory responses across different threats. |
| Keywords: | Innovation, regulation, lobbying, innovation systems, ban |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:wpaper:201908&r=all |
| By: | Diekhof, Josefine; Eckl, Verena; Krieger, Bastian; Licht, Georg; Nguyen, Thu-Van; Peters, Bettina; Rammer, Christian; Stenke, Gero |
| Abstract: | The exchange of knowledge between science and industry has been a focus of innovation research and policy for many decades. New developments in the way technologies are generated, shared, and transferred into new products, services, and business models are currently re-emphasising science-industry interactions. Main drivers are the emergence of open innovation models, the increased internationalisation of innovation processes, the rise of digital platforms, new modes of governance in public research, and the enlarged role of disruptive innovations. At the same time, the measurement of knowledge flows is still limited, and indicators on recent trends in science-industry interaction are lacking. This limits innovation policy in monitoring changes and addressing challenges. A conference in October 2019 in Berlin brought together industry representatives, researchers, and policy makers to discuss these developments and how the measurement of science-industry links could be improved. This policy brief summarises key trends in science-industry collaborations, presents existing indicators and discusses ways to improve our indicator system on knowledge flows between science and industry in order to better inform policy. |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewpbs:92019&r=all |
| By: | Sandro Montresor (School of Advanced Studies, Gran Sasso Science Institute); Antonio Vezzani (Roma Tre University) |
| Abstract: | We investigate the extent to which financial constraints hamper the firms’ investment in intangibles. Drawing on the extant literature, we maintain that a distinction should be kept between innovators and non-innovators. Moreover, we argue that such a distinction should be investigated along the whole spectrum of intangibles firms invest and by addressing the risks of reverse causality and simultaneity bias in the relationship. Through an original quasi-panel extension of a recent European Innobarometer survey, we estimate two sets of recursive bivariate probit models – for innovative and non-innovative firms’ investments – from which interesting results emerge. Financial barriers hamper the investment of both kinds of firms only for R&D, design, and organisation and business processes. With respect to other intangibles, instead, financial barriers act only on innovators (or non-innovators) or are even absent. Furthermore, the hampering role of financial barriers distributes differently across different intangibles between innovators and non-innovators. |
| Keywords: | &D, intangibles, innovation, financial barriers. |
| JEL: | O30 O32 O33 |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:wpaper:201907&r=all |
| By: | Christos Karydas (Center of Economic Research (CER-ETH), ETH Zurich, Switzerland); Evangelos V. Dioikitopoulos (King's Business School, Group of Economics, King's College London, UK) |
| Abstract: | This paper argues that the joint relation between long-term orientation, environmental quality and innovation plays a key role in explaining environment-poverty traps. Based on empirical observations, we allow for the subjective discount rate to negatively depend on environmental quality in an R&D-driven endogenous growth model with local pollution externalities. Our model reconciles two empirical facts: i) multiple equilibria of economic and environmental development; ii) opposite responses to technological improvements depending on the initial equilibrium. Our results suggest that -- in addition to traditional policies such as development aid and technology transfer -- policies that aim at improving both the economic and the environmental dimension of sustainability, should also focus on changing individuals' long-term views in countries that face weak environmental conditions. |
| Keywords: | Endogenous growth, innovation, time preference, environmental poverty traps, economic poverty traps |
| JEL: | D90 E21 O13 O44 Q55 Q56 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:eth:wpswif:20-330&r=all |