2.7.2.3 The public-sector role in technological change
Given the importance of technology in determining both the magnitude of future GHG emission levels as well as feasibility and costs of emission reduction efforts, technology policy considerations are increasingly considered in climate policy analyses. Ongoing debate centers on the relative importance of two differing policy approaches: technology-push (through efforts to stimulate research and development) and demand-pull (through measures that demand reduced emissions or enhanced efficiency). Technology-push emphasizes the role of policies that stimulate research and development, especially those aimed at lowering the costs of meeting long-term objectives with technology that today is very far from economic in existing markets. This might include such measures as public-funded R&D or R&D tax credits. Demand-pull emphasizes the use of instruments to enhance the demand for lower-emission technologies, thereby increasing private incentives to improve these technologies and inducing any learning-by-doing effects. Demand-pull instruments might include emissions taxes or more direct approaches, such as renewable portfolio standards, adoption subsidies, or direct public-sector investments (see Figure 2.3).
Two market failures are at issue when developing policies to stimulate technology development. The first is the failure to internalize the environmental costs of climate change, reducing the demand for climate-friendly technologies and thereby reducing private-sector innovation incentives and learning-by-doing. The second is a broad suite of private-sector innovation market failures that hold back and otherwise distort private-sector investment in technological advance, irrespective of environmental concerns (confer Jaffe et al., 2005). Chief among these is the inability to appropriate the benefits of knowledge creation. From an economic standpoint, two market failures require two policy instruments: addressing two market failures with a single instrument will only lead to second-best solutions (see, for example, Goulder and Schneider, 1999). Hence, it is well understood that the optimal policy approach should include both technology-push and demand-pull instruments. While patents and various intellectual property protection (e.g. proprietary know-how) seeks to reward innovators, such protection is inherently imperfect, especially in global markets where such protections are not uniformly enforced by all governments. Similarly, in the early adoption of technology learning-by-doing (by producers) or learning-by-using (by consumers) may lower the cost to all future users, but in a way that may not fully reward the frontrunners. Similarly, lack of information by investors and potential consumers of innovative technologies may slow the diffusion of technologies into markets. The ‘huge uncertainties surrounding the future impacts of climate change, the magnitude of the policy response, and thus the likely returns to R&D investment’ exacerbate these technological spillover problems (Jaffe et al., 2005).
The outstanding questions revolve around the relative combinations of instruments and around how effective single-policy approaches might be. Within this context, a number of authors (e.g. Montgomery and Smith, 2005) have argued that fundamental long-term shifts in technology to mitigate greenhouse gas emissions cannot be achieved through emissions-constraining policies alone, and short-term cap and trade emission-reduction policies provide insufficient incentives for R&D into long-term technology options. Conversely, Popp (2002) demonstrated how energy R&D is responsive to price signals, suggesting that without emissions constraints R&D into new low-emission technologies may face a serious lack of incentives and credible policy signals. The argument that emissions-based policies will induce long-term technology innovation relies primarily on two lines of reasoning (Goulder 2004; Grubb, 2005). The first is that the anticipation of future targets, based on a so-called announcement effect, will stimulate firms to invest in research and development and ultimately to invest in advanced, currently non-commercial technology (the credibility and effectiveness of this effect, however, being challenged by Montgomery and Smith, 2005). The second is that early investment, perhaps through incentives, mandates, or government procurement programmes, will initiate a cycle of learning-by-doing that will ultimately promote innovation in the form of continuous improvement, which will drive down the cost of future investments in these technologies. This issue is especially critical in the scaling up of niche-market applications of new technologies (e.g. renewables) where mobilizing finance and lowering investment risks are important (see, for example, IEA, 2003, or Hamilton, 2005). In their comparative analysis of alternative policy instruments Goulder and Schneider (1999) found that when comparing a policy with only R&D subsidies to an emissions tax, the emissions-based policies performed substantially better.
Irrespective of the mix between demand-pull and technology-push instruments, a number of strong conclusions have emerged with respect to the appropriate policies to stimulate technological advance. First, it is widely understood that flexible, incentive-oriented policies are more likely to foster low-cost compliance pathways than those that impose prescriptive regulatory approaches (Jaffe et al., 2005). A second robust conclusion is the need for public policy to promote a broad portfolio of research, because results cannot be guaranteed since it is impossible to ex ante identify
technical winners or losers (GTSP, 2001). A third conclusion is that more than explicit climate change or energy research is critical for the development of technologies pertinent to climate change. Spillovers from non-energy sectors have had enormous impacts on energy-sector innovation, implying that a broad and robust technological base may be as important as applied energy sector or similar R&D efforts. This robust base involves the full ‘national systems of innovation’ involved in the development and use of technological knowledge. Cost and availability of enabling infrastructure can be especially important factors that limit technology uptake in developing countries. Here enabling infrastructure would include management and regulatory capacity, as well as associated hardware and public infrastructure.