Energy R&D Investments and Emissions Abatement Policy.

AuthorYin, Di

    Climate-economy models attempt to estimate and compare the benefits and costs to slow down global warming. The molecules of carbon dioxide, once emitted from various sources such as combustion, stay in the atmosphere for 50 to 200 years. (1) When the long-term emissions abatement policy is dealt with, it is important to take into account the interaction between the emissions abatement policy and energy technological progress because the impact of energy technological progress is typically realized over a long-time horizon. Figure 1 shows how C[O.sub.2] emissions are affected by the energy technological progress driven by energy R&D investments.

    The energy R&D investments can be categorized into two main groups: energy R&D investments in energy efficiency and energy R&D investments in backstop technology. (2) The R&D investments in energy efficiency enhance the energy supply chain such as production, transformation, and consumption to deliver more energy services given the same amount of primary energy. for example, the light-emitting dioxide (LED) technology saves 75% energy compared to traditional halogen (IEA, 2017a). Electric vehicles improve fuel efficiency compared to the internal combustion engine vehicles (IEA, 2017a). The improvement in energy efficiency reduces C[O.sub.2] emissions, thus directly affects the emissions abatement policy.

    Energy R&D investments also expand the system scale of backstop technology, such as solar photovoltaic (PV) energy and wind energy (IEA, 2013, 2014). For example, the installed solar photovoltaic (PV) capacity has increased dramatically since 2010 than in the previous forty decades (IEA, 2017b). The amount of electricity generated by the PV system around the world grew by 50% in 2016. The PV's share of global electricity is expected to reach 16% by 2050 forecasted by (IEA, 2017b). Wind power deployment has more than doubled since 2008. Wind power generation targets 15% to 18% share of global electricity (IEA, 2015). System expansion lowers the operation and maintenance costs, hence, reduces the price per unit backstop energy, which enhances the competitive advantage of backstop technology.

    Energy R&D investments in backstop energy affect C[O.sub.2] emissions indirectly through changing the energy compositions and energy substitutions. The energy compositions reflect the mixed energy demand in a specific sector. Table 1 indicates the heterogeneity of the energy composition among different sectors. Oil products are widely used in the transportation sector, coal and coal products are mainly used in the industry sector, and natural gas is largely used in the residential sector. Furthermore, the energy composition is dynamic rather than static. Figure 2 shows that the growth rate of each energy product is imbalanced over the years. Coal and coal products experienced a high growth rate from 2000 to 2010 but experienced a relatively low growth rate from 2010 to 2015. Solar and wind energy grow much faster than all the traditional energy resources did from 2005 to 2015. The changes in the energy composition indicate that inter-fuel substitutions are evident in different sectors. They result in changes in carbon emissions because of varying emissions coefficients of fossil fuels. (3)

    The energy substitution is determined by the Ricardian comparative advantage that the energy with the comparative advantage, i.e., the one with the least cost, is first used in production. The comparative advantage of the energy changes endogenously over time due to two factors: the scarcity rent and the energy R&D investments. If a resource is not abundant, or it is scarce, the resource with an initial comparative advantage, i.e., a low cost, tends to lose its advantage as the scarcity rent increases. For example, coal was used at a lower cost than natural gas in the power sector. As natural gas booms in recent years, the scarcity rent of natural gas decreases significantly, which results in coal losing its comparative advantage and being replaced by natural gas in the power sector. The energy R&D investments in backstop energy lower the cost of the backstop technology and thus improve its comparative advantage compared to fossil fuels. It is interesting to see how the R&D investments in the backstop energy affect energy substitution and further alters the C[O.sub.2] emissions abatement policy.

    We develop a new model named ENdogenous Energy R&D (ENER) model to incorporate the energy R&D investments and endogenous energy substitution into the climate-economy model. The ENER model has two distinct innovations. First, the model explicitly identifies the roles of R&D investments in energy efficiency and in backstop technology. It evaluates the impacts of energy R&D investments and the abatement policy on energy substitution, economic gains, and abatement costs. Second, it constructs a 2-sector 3-production-factor model that emphasizes the micro-foundation of energy substitution. The ENER model represents detailed energy demands that enable us to analyze inter-fuel substitution in each sector of an economy and to predict how soon the backstop energy replaces fossil fuels.

    With the more realistic model, this study attempts to examine (a) the optimal policy of energy R&D investments, the optimal abatement policy, and the interaction of two; (b) the sequence of energy substitution; (c) economic gains and abatement costs, and (d) the climate impact. With the innovations made in the ENER model, this study expects to contribute to the literature in four areas. First, the study explores the different roles of two R&D investments and examines the interaction between energy R&D investments and the abatement policy. Second, the study investigates endogenous inter-fuel substitution given various energy R&D investments and abatement policies. We try to answer how soon the energy use will transit to backstop technology from fossil fuels. Third, the study estimates economic gains and abatement costs with the emissions abatement policies incorporating two types of energy R&D investments. Fourth, the study presents the possible temperature changes caused by C[O.sub.2] emissions and shows the control rates given different abatement policies.

    The rest of the study is organized as follows. Section 2 presents a literature review focusing on three research streams related to the energy technological change, energy substitution, and climate-economy models. Section 3 formulates the model. Section 4 presents policy scenarios, data collection, and how the model is calibrated to deliver robust and significant results. Section 5 discusses the trajectory of energy R&D investments, the trajectory of abatement policy, and performance comparison with respect to the sequence of energy substitution, economic gains, abatement costs induced by various emissions abatement policies, and temperature changes. Section 7 concludes the study.


    This study is closely related to three research streams. The first stream is energy technological progress. Jamasb and Kohler (2007) and Kahouli-Brahmi (2008) are excellent surveys summarizing how to model the learning curve for energy technology. Two approaches to model the technological progress are the 'learning-by-doing' approach and the 'learning-by-researching' approach. The 'learning-by-doing' approach (Benthem et al., 2008; Grubler and Messner, 1998; Liu and Wei, 2016; Marine and Richels, 2004) models that the energy cost is reduced by experience accumulation with a one-factor learning curve. The 'learning-by-researching' approach (Barreto and Kypreos, 2004; Miketa and Schrattenholzer, 2004) models that the energy cost is lowered by R&D investments and experience accumulation with a two-factor learning curve. To capture the feature of energy R&D investments, this study adopts a 'learning-by-researching' model. Extending the existing studies, this model explicitly identifies two types of energy R&D investments: R&D investments in energy efficiency and R&D investments in backstop energy. This study concludes that the two types of energy R&D investments play different roles in energy substitution and C[O.sub.2] reduction.

    The second stream of research is related to the phenomenon called endogenous energy substitution. The endogenous substitution among resources is studied by Endress and Roumasset (1994) and Chakravorty et al. (2005). The specialization of resources according to demand is driven by Ricardian comparative advantage, which leads to an endogenous energy substitution. The endogenous energy substitution reflects heterogeneous demand and the simultaneous extraction of energy resources in an economy. Recent works related to energy transition include Court et al. (2018), Hartley et al. (2016), and Hartley and Medlock (2017). Their studies explore the displacement of fossil fuels by the alternative resources in the framework of growth model. Complementary to their work, our research examines the energy transition given various energy R&D investments and various abatement policies.

    The third stream of research is related to the climate-economy model, which are from three broadly defined approaches: the top-down approach, the bottom-up approach, and the hybrid approach. Top-down models (Nordhaus, 1994, 2014; Popp, 2004) incorporate energy into a macro-economic framework, where energy is a third production factor along with capital and labor. They evaluate emissions abatement policies and other macroeconomic variables in the macroeconomic and/or general equilibrium framework. Bottom-up models (EIA, 2008; Greene et al., 2004; Yi et al., 2019) have detailed representation of technologies of the energy system. They minimize end-use energy costs and choose energy transformation technology with the lowest costs. Hybrid models link the bottom-up model and the top-down model together. Most studies confine the research interests in the energy system of a...

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