The role of cross-country knowledge spillovers in energy innovation

1. The role of cross-country knowledge spillovers in energy innovation Paola Garrone, Lucia Piscitello, Yan Wang

2. Objectives • To obtain evidence on the effect of cross-country knowledge spillovers on renewable energies technologies • To obtain evidence on the channels through which technological knowledge diffuses internationally in renewable energy technologies (e.g. geographical proximity, cross-country interactions)

3. Motivations • Current and future relevance of the markets of renewable energy technologies • The demand for these green technologies is growing in both advanced and developing countries, due to environmental, social and economic drivers (fostered by energy-climate policies) • How to enter the technological race / market arena? • Only few countries account for most of the world’s creation of new techology, and for most other countries, foreign sources of technology account for 90 percent or more of domestic productivity growth (Keller 2004) • The diffusion of new energy innovation at the international level plays an important role given the highly concentrated innovation activities of few industrialised countries

5. Background • International diffusion of technological knowledgetakes 2 basic forms (Keller 2004; Pizer and Popp 2008) • One ismarket transactions (e.g. Firms make royalty payments for patents or licenses developed abroad) • The other is international knowledge spillovers What is knowledge spillover/ technology spillover? It means that the investor can not fully appropriate the return on R&D investment, it always creates benefits to other individuals other than the inventor. This external effect is called knowledge spillover

6. The literature on energy innovation • The impacts of technology and environmental policies on energy technology innovation (Taylor 2008; Garrone and Grilli 2010; Popp 2010; Johnstone et al., 2010; Dechezlepretre et al. 2010) • Technology-push policies (e.g. Public R&D budgets) • Demand-pull policies (e.g. Feed-in tariffs) • The diffusion of carbon-freeenergy technologies and energy-efficient technologiesat the national level and at the international scope(Popp et al. 2011; Dechezlepretre et al. 2008; Hascic and Johnstone 2009; Verdolini and Galeotti 2011) • As far as the cross-country knowledge spillovers in the energy sector is concerned, it has been recognized that cross-country knowledge spillovers have a significant impact on the innovation activity of countries (e.g. Bosetti et al. 2008; OECD 2008)

7. The literature on knowledge spillovers • Most empirical analysis use R&D spillover regression to study international spillovers, with TFP as a dependent variable • Analyses have been extended to analyse particular channels for the spillovers, and the most frequent channel that has been explored is international trade (e.g. Coe and Helpman 1995) • A variant of this approach replaces TFP by the number of patents (e.g. Jaffe 1986; Braun et al. 2010) • Another stand of study uses patent citation as a proxy of knowledge flows between different innovating firms, regions or countries (Trajtenberg 1996; Verdolini and Galeotti 2011)

8. The literature on knowledge spillovers • Non-codified (tacit) nature of technological knowledge (Keller 2004) • Tacit knowledge is less accessible and harder to diffuse as it relies more on face to face contacts (Bottazzi and Peri 2003) • Similar ideas of connectivity have been deployed to argue that transnational linkages lead to the spread of environmentally superior innovations to developing countries, which contribute to domestic improvements in environment efficiency (Neumayer 2009)

9. Research question • Does international R&D stocks in renewable energies have positive effects on domestic innovation? • If so, it is important to understand how they can be reaped and under which conditions technological laggard countries can exploit them • We distinguish three kinds of international knowledge spillovers: • Knowledge spillovers that can diffuse without particular channels because of, the global reach of computers and online documents, etc • Knowledge spillovers that is impeded by geographic distance • Technological knowledge that is more tacit and less codified and as such need repeated contacts and interactions to be exchanged

10. Methodology • A panel of 18 OECD countries, 1990-2006, 301 observations • Negative binomial fixed effect count data model • Knowledge production function • Core variables: • domestic knowledge stocks; international knowledge stocks; human capital • Innovation: patent count in renewable energy technologies • Renewables: wind, solar, geothermal, ocean, biomass and waste (Johnstone et al. 2010) • Patent data from the EPO World Patent Statistical database (PATSTAT 2010) • Econometric framework: • RPAT is the number of patent filed by the inventor of country i in year t • HC is the human capital of country i in year t-1 • DRD is the domestic knowledge stocks of country i in year t • CCKS is the knowledge spillover variable (POL; DIS; TRF)

11. Variables • Domestic knowledge stock (DRD) are constructed according to the perpetual inventory method (with a decay rate of 5%) • Public R&D expenditures (RD) in renewable energies (IEA 2010) are used to construct the knowledge stocks • Three indicatorstorepresent cross-country knowledge spillovers: • The first indicator POL is an un-weighted pool of R&D stocks in all other countries in the sample

12. Variables • Three indicators for cross-country knowledge spillovers: • The second indicator DIS has been constructed by aggregating the other countries’ R&D stocks through inverse functions of geographic distance (Xu and Wang 1999) • The third indicator TRF has been obtained by using the bilateral trade flows as weights to aggregate the donor countries’ R&D stocks

13. Variables • Human capital (HC): the average years of schooling for people over 25, as provided by Barro-Lee (2010) • Control variables: • CGI: the ratio between capital goods import from the world and GDP of the focal country • GDP • FIT:guaranteed prices • REC:energy certificate • OB: obligations (e.g. portfolio standards, quota systems)

14. Empirical results Table 1 – Fixed effect negative binomial model Standard errors in parentheses, *p < 0.05, **p < 0.01, ***p < 0.001

15. Empirical results Table 3 – Variation in the number of patents in renewable energy technologies, simulations ns: not significant ^: the standard variation is the ratio between the sample standard deviation and mean

16. Robustness check Table 2 – Fixed effect negative binomial model, excluding GDP Standard errors in parentheses, *p < 0.05, **p < 0.01, ***p < 0.001

17. Empirical results • Preliminary findings confirm that technological knowledge can be sourced internationally if the focal country maintains repeated contacts, exchanges and interactions with the countries that invest more intensely in public research • International technological knowledge is of little use to countries that have not established interaction channels with R&D-active partners, whether geographic distances are limited or not

18. Conclusions • Public energy R&D expenditures are a key input to innovation in the field of renewable energies, i.e. a relevant element in global efforts toward carbon stabilization. Coordination between advanced countries is warranted to reduce the risk of free-riding in energy-climate innovation • International technology diffusion in the renewable energy sector seems not to be uniform. As far as disembodied technological knowledge is concerned, it is more likely to flow between countries which have developed more intense mutual relations

19. Thank you