Three essays on energy policy, climate change, and economic development

Abstract

(Chapter 1) Renewable energy (RE) electricity plays a crucial role in addressing climate change but has limitations, such as intermittent production, high costs, and site constraints. South Korea transitioned its RE support system from a feed-in tariff (FIT) to a renewable portfolio standard (RPS) in 2012. This study evaluates the impact of the FIT-to-RPS transition on cost reduction for non-photovoltaic RE technologies (RETs), i.e., onshore wind power, bioenergy power, small hydropower, and fuel cell power, using a learning curve model. The results indicate that the FITto-RPS transition did not have a significant positive impact on cost reduction for onshore wind power, bioenergy power, or small hydropower, as the results show negative learning rates (LRs) during both FIT and RPS periods. The analysis suggests that the positive learning effect was hindered by the gradual depletion of sites favourable to RE power plants as more RE power plants were installed. However, fuel cell power, which is not affected by land availability, increased the LR from 1.4% to 3.5%. This study has policy implications, such as improving excessive regulations and procedures that hinder the installation of RE power plants on sites with good condition. (Chapter 2) Economic growth, CO2 emissions, and energy mix are interrelated, and their relationship has been analysed using various dynamic models. The Vector Autoregressive (VAR) model, treating all factors as endogenous, has been commonly used to study this relationship. However, reduced form VAR, which do not account for contemporaneous effects, may misrepresent the impact of energy policies. In contrast, the Structural VAR (SVAR) model which include contemporaneous effects, provide a more accurate evaluation of energy policy impacts. This study applies both reduced form VAR (IRF) and SVAR (OIRF) to South Korea and Japan. The IRFs from reduced form VAR indicate that in South Korea, the electricity mix does not causally affect CO2 emissions, while both fossil fuel and renewable electricity positively affect CO2 emissions in Japan. However, OIRFs from SVAR reveal that fossil fuel electricity significantly increases CO2 emissions in both countries, while renewable electricity significantly reduces emissions in Japan. These findings suggest that SVAR provides a more accurate assessment of energy policies' environmental impacts than reduced form VAR, warranting caution with VAR results. (Chapter 3) This study examines the impact of the energy mix and economic growth on CO2 emissions in 12 countries with nuclear power plants and 10 countries without, among OECD members, from 1971 to 2021, utilizing a dynamic panel ARDL model. The findings support the Environmental Kuznets Curve (EKC) hypothesis in countries with nuclear power but not in those without. Replacing fossil fuel electricity (FE) with renewable electricity generation (RE) or nuclear energy generation (NE) significantly lowers CO2 emissions in both groups in the long-run, and RE proves more effective than NE in nuclear-powered nations. Moreover, substituting FE with RE shows greater emissions reduction in countries lacking nuclear power plants. While trade openness has insignificant effect, population growth exerts a notable influence in both groups. To check the robustness of the ARDL results, same ARDL model with sub-sample group was also conducted, and the analysis of the subsample group shows similar results to those of the original ARDL results. The policy implications are that economic growth contributes to emissions reduction in the long-run for countries with nuclear energy, but this benefit is absent in countries without nuclear power, stressing the need for additional policy measures to curtail emissions.