Several jurisdictions have announced unilateral climate policy ambitions for the coming decades. The cost of imposing a domestic cap will heavily depend on whether the domestic policy design generates the most cost-effective projects within the respective jurisdictions. Even though the usual recommendation for optimal abatement is uniform emissions pricing, market failures or other inefficiencies may render emissions pricing insufficient. This study addresses one such case that may arise if policymakers prove unable to credibly commit to future policy. Several socially cost-effective abatement options involve upfront investment, and these may be hampered if politicians prove unable to commit to future policies and instead leave it up to future politicians to do so. Indeed, even if the same politicians remain in office, there is an inherent time inconsistency problem in their behaviour that tends to discourage investments. If agents take on immediate investment costs in response to announced future ambitions and emission prices, future prices need only to encourage operations and service of the instalments in the future and can be set lower than earlier announced. On the other hand, if agents do not invest today, future abatement costs will be substantially larger than assumed by current policymakers, and optimal ambitions will fall; see Blackmon and Zeckhauser (1992). Whether the source of commitment failures in climate policy is time inconsistency or the inability of politicians to commit their successors, the phenomenon may impede the diffusion of available climate technologies (Ulph and Ulph, 2013: Brunner et al., 2012).
Quantification of the potential inefficiencies of such regulatory uncertainty is scarce in the literature. The main purpose of this study is to compare the costs of mitigating national greenhouse gas (GHG) emissions under different policy designs, given that upfront investment in climate technologies is hampered by the inability of policymakers to signal trustworthy ambitions. When emissions pricing is perceived as short-lived, upfront investment in climate technologies will not appear profitable; firms will instead reduce their variable costs and scale down output, while consumers will respond by substituting other consumer goods for energy, and leisure for consumption (Spiller, 1996). We numerically analyse the consequences in terms of abatement costs and lack of technological change and evaluate alternative policy responses to such regulatory uncertainty, including a guarantee scheme and an upfront investment subsidy scheme.
Bosetti and Victor (2011) numerically study commitment problems of a global emissions pricing system and assume the view of economic agents in powerful states, which differs from our perspective of a small, ambitious country. They argue that, due to the lack of supranational legal institutions, problems with confidence in international agreements may be even more serious than problems with confidence in decisions that are taken by large states. For small states, however, unilateral ambitions imply taking on extra costs without reaping obvious climate gains. This could easily become more politically controversial, less reliable and, thus, more costly than taking part in a binding international agreement. Furthermore, it is often the case that the smaller the coalition, the smaller the variety of emission sources and, consequently, the more expensive the abatement. Countries showing a willingness to act are also likely to have tried out the cheaper options already.
Numerically assessing mitigation strategies and abatement costs under various policy regimes requires a computational model that allows for abatement both within and beyond existing technologies. For this purpose, we developed a computable general equilibrium (CGE) model which, besides including options of downscaling emission-intensive activities and substituting factors within existing technologies, accounts for potential endogenous changes in climate technologies. This is in contrast to conventional CGE models, which lack technological responsiveness beyond historically observed practice and, thus, tend to overestimate abatement costs. On the other hand, technology-rich models like traditional energy system models exclude realistic flexibility of economies that stems from existing, profitable downscaling options both in supply and demand and from cost-shifting opportunities among market agents. Ours combines the strengths of the two model traditions.
CGE modelling of induced climate technological progress has blossomed during the recent decades, with research and development (Goulder and Schneider, 1999) or learning by doing (Gerlagh and Lise, 2005) being the main endogenous mechanisms. A fairly recent survey of the literature is given in Gillingham et al. (2008). Several well-established, global CGE models have included such mechanisms, including the ENTICE (Popp, 2004), WIAGEM (Kemfert, 2005) and WITCH (Bosetti et al., 2006) models. Some models are also developed for national technology policy studies, early birds being Heggedal and Jacobsen (2011) for Norway and Bretschger et al. (2011) for Switzerland. However, our ambition is different and complementary to these; we endogenise the adoption of climate technologies rather than their abatement productivity. The main justification for keeping productivity given in our analysis is that we look at the small, open economy case where productivity change depends on the largely exogenous movement of the global technology frontier.
Our adoption module is more comparable to the recent years' large-scale hybrid approaches; see Bataille et al. (2009), Bosetti et al. (2006), and Laitner and Hanson (2006). In relation to these, it stands out by being simple and easily applicable while at the same time being capable of representing, with good approximation, a variety of potential technological options. We expand the scope compared to other contributions in the field by not limiting the technological adaptation possibilities to the energy supply side. Instead, our model allows for investment in climate technologies within energy-intensive industries. Our approach has most in common with the modelling of industry-specific marginal costs of transport technologies in Kiuila and Rutherford (2013). Ours does, however, have the advantage of avoiding adjustments of the social accounts matrix when including abatement costs. This property makes updating of the adoption module to new base years, more industries, or novel technological information less challenging. Moreover, we include technological options in petroleum extraction and several energy-intensive process industries along with in transport, the latter involving investments in households, private firms and public services. The technological options with their costs and abatement potentials are easy traceable in the modelled representation.
Our analysis considers Norway's ambitious domestic target, representing an approximate 20-per-cent cut in GHG emissions in 2020 from an official reference scenario prolonging current and decided policies. We find that the most cost-effective commitment device--a guarantee scheme that ensures long-lasting commitment to a uniform emissions pricing scheme--implies an economy-wide welfare loss of 1/4 per cent, or about EUR 25 per capita as a yearly average. In this cost-effective regime, more than half of the necessary reduction is achieved by choosing more climate-friendly technological solutions. The rest is obtained by scaling down relatively emission-intensive industries and consumption activities. In other words, abatement at this ambitious level is not overwhelmingly costly. However, failure to implement a reliable, enduring climate policy more than triples the abatement costs compared to the scenario with the guarantee scheme. When technology options are ruled out, the main extra costs fall on traditional manufacturing firms and some of these industries shut down most of their activity, typically in regions with few alternative job opportunities. Subsidising upfront investment in climate technologies is a feasible policy option. The cost of raising funds is found to be minor. Finally, note that the case where technological options are ruled out also serves to illustrate the outcome of a traditional CGE analysis. Our findings indicate that traditional CGE models significantly overestimate the costs of the first-best policy--in our case by a factor of 3.
The hybrid model is presented in Section 2, while Section 3 reports from the analysis. Section 4 concludes and discusses some contributions and caveats.
MSG-TECH, a CGE-based hybrid model of the Norwegian economy, is a recursively dynamic, integrated economy-energy-emission model with endogenous climate technology options. (1) It specifies 60 commodities and 40 industries. Financial capital is perfectly mobile across borders, while real capital and labour are perfectly malleable and can be smoothly reallocated within the economy. (2) As the economy is small, all agents face exogenous world market prices and interest rates (the exchange rate is numeraire). The model gives a detailed description of the empirical tax, production, and final consumption structures. Several second-best features due to market imperfections or policy interventions are modelled, including taxation of labour and existing industrial policies. In addition, barriers to climate technology investment can be represented.
Consumers are represented by a single average consumer whose utility in every period depends on the consumption of leisure and of 26 different consumer goods organised in a CES structure; see Figure A.2 in the appendix. Environmental benefits are not accounted for. Consumer goods are specified at a detailed level with a view to capturing important substitution possibilities...
Diffusion of Climate Technologies in the Presence of Commitment Problems.
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