Impact of domestic energy-efficiency policies on foreign innovation: The case of lighting technologies
Introduction
A recent U.S. National Academies report suggests that feedback forces could push the Earth System toward a self-reinforcing condition of continued global warming (Steffen et al., 2018). Constraining global temperature to well below 2 °C above pre-industrial levels will require developing low-carbon energy technologies and deploying them with well-designed energy and environmental policy instruments (Brown and Sovacool, 2014).
To design effective energy and environmental policy instruments, ex-post econometric policy evaluation is important as it reveals the consequences of policy instruments (e.g., innovation). A significant body of research has examined the impact of energy and environmental policy on technological innovation by using patent data (Carrión-Flores and Innes, 2010, Costantini et al., 2015; Verdolini and Galeotti, 2011; Noailly and Ryfisch, 2015). It has documented a positive relationship between policy and technological innovation that is known as the “policy inducement effect” (Brunnermeier and Cohen, 2003, Jaffe and Palmer, 1997, Johnstone et al., 2010, Popp, 2002). Specifically, these studies have investigated a significant impact of domestic policies on domestic environmental innovation. However, few studies have examined international technology diffusion in response to policy instruments.
An initial effort to expand the impact of domestic policy on domestic technological innovation was undertaken by Lanjouw et al. (1996) who analyzed the effect of domestic policy on foreign innovation. They conclude that strict vehicle emission regulations in the United States (U.S.) spurred innovation in Japan and Germany. Popp (2006) found that strengthening U.S. standards led to more patenting in the U.S., but not internationally. Subsequently, Popp et al. (2011) identified a positive correlation between domestic and foreign regulation and innovation, and others have found that foreign policies affect cross-border innovation diffusion (Dechezleprêtre and Glachant, 2014, Dechezleprêtre et al., 2015). Building on the stream of literature on the international diffusion of low-carbon technologies (Dechezleprêtre and Glachant, 2014, Dechezleprêtre et al., 2013a, Peters et al., 2012), this paper tests the impact of domestic energy-efficiency policies on foreign patenting within the empirical context of lighting technologies. We pose the following inquiries: First, what role do these domestic demand-pull and technology-push policies play in inducing compact fluorescent lamps (CFLs) and light-emitting diodes (LEDs) patenting? Second, does domestic demand-pull and technology-push policies affect foreign lighting patenting?
The rest of the paper is organized as follows. Section 2 introduces background information and relevant theories. Section 3 describes the dataset construction. Section 4 describes the empirical methodology and econometric models. Findings are discussed in Section 5, and in 6 Discussion, 7 Conclusions and policy implications we discuss conclusions and policy implications.
Section snippets
Background
Lighting accounts for about 10% of the total electricity consumed in the U.S.3 According to one International Energy Agency (IEA)’s report, the potential amount of electricity that could be saved in building lighting by 2030 is equivalent to the entire electricity consumed in Africa in 2013.4
Reflecting on the history of technological development in lighting, light
Dataset construction
To test the impact of domestic energy-efficiency policies on foreign patenting within the empirical context of lighting technologies, several datasets are constructed. To measure the dependent variable, we collected patent data from the European Patent Office (EPO)/Organization for Economic Cooperation and Development (OECD) World Patent Statistical Database (PATSTAT)10 to
Empirical methodology
First, we estimate the effect of domestic demand-pull and technology-push policies on domestic lighting patenting. The dependent variable is the number of patent application in country i in year t. An econometric model is constructed as follows:Where = 1,….,19 refers to the country and = 1992,…,2007 refers to time. MEPS is the average minimum energy efficiecny standards of fluorescent lamps. MEPS_CFL indicates the average minimum
Effect of domestic policies on domestic patenting
Table 3 shows the effects of domestic policies on domestic patenting. It indicates that the demand-pull policies represented by MEPS are statistically significantly positive in both technologies. Note that the magnitude of LEDs’ MEPS coefficient is greater than that of the CFLs’ coefficients. The results provide evidence of a positive relationship between domestic demand-pull energy efficiency policies on domestic lighting patenting. It also shows that the technology-push policies represented
Discussion
Based on the estimation results, we find evidence that establish a strong correlation. First, we use patent data to examine the effect of domestic demand-pull and technology-push policies on domestic innovation activity in lighting technologies between 1992 and 2007. We find that both domestic demand-pull and technology-push policies positively affect domestic lighting patenting that is consistent with previous studies such as Dechezleprêtre and Glachant (2014) and Peters et al. (2012).
Second,
Conclusions and policy implications
This paper identifies the effect of domestic demand-pull and technology-push energy-efficiency policies on domestic and foreign patenting in the field of lighting technologies. We find strong correlational evidence linking both domestic demand-pull and technology-push policies with domestic lighting patenting. We also find strong correlational evidence of a significant and positive relationship between domestic demand-pull policy and foreign lighting patenting. This is consistent with a causal
Acknowledgements
PATSTAT is supported by the Enterprise Innovation Institute at Georgia Institute of Technology. We acknowledge constructive comments from members of the Climate and Energy Policy Laboratory at Georgia Tech, the Atlanta Conference on Science and Innovation Policy, WORP, the ETH Academy on Sustainability and Technology, 41st IAEE International Conference, 6th World Congress of Environmental and Resource Economists, and members of the Energy Club at Georgia Tech. We have benefited from discussions
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Permanent Address: Zuckerman Institute for Connective Environmental Research, School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK.
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