Human activities have caused widespread, rapid, and intensifying climate change. Overshooting 1.5 ◦C is inevitable in 2024, while substantial scientists have warned that irreversible changes will settle down in many places over the Earth after a 2 ◦C increase since 1850-1900. We must find a way to mitigate climate change, study its impact on our society, and build sustainable communities. Nevertheless, it isn’t easy to find a socially desirable implementation of an environmental policy due to its complexity and various stakeholders. This dissertation contributes to finding socially desirable ways of tackling climate change in energy transition.The first chapter, titled “Incentivizing capital investments in electric vehicle attributes to stimulate demand,” studies the optimal subsidization of electric vehicles (EV) by stimulating investment in industries. Aggressive automobile emissions reductions are required to tackle climate change. The US government has subsidized electric vehicles (EV) with a constant purchase subsidy of $7500 to promote the transition from internal combustion engines (ICE). In this chapter, I analyze the optimal subsidies for EV adoptions, considering both purchase and investment subsidies. The theoretical model includes firms’ dynamic Bertrand game of price and investment and a government’s dynamic Stackelberg game with firms. Firms maximize their benefit with price and investment decisions under a fixed number of new market sales yearly. Experience curve decreases their unit production cost and increases the attribute as capital accumulation. Consumers discreetly choose vehicles with price and attributes. Governments maximize social net benefit with subsidy decisions considering all surplus, expenditure, and social costs of carbons. I run this theoretical model by estimating data for every vehicle model sold in the US from 2008 to 2019 and calibrating the model by the collocation method. I show that the two dynamic policies have the same trend, in which the optimal intervention begins at high values to spur early adoption before falling and approaching zero as EV firms’ capital grows. In the two dynamic policies, the optimal policy intervention is very high at the capital level in 2024: $10694 to $16073 (purchase subsidy) and $17.06 billion to $40.58 billion (investment subsidy). Then, the optimal policy shrinks rapidly as EV capital increases. The optimal path leads us to the equilibrium where ICE capital becomes much less, while EV capital remarkably increases compared to zero policy. Dynamic purchase and investment subsidy increase the total net present value social net benefit by $2.32 trillion (3.84%) and $1.44 trillion (2.39%) compared to zero policy and by $923 billion (1.49%) and $47.7 billion (0.08%) compared to the current constant policy. It sheds light on the optimal market intervention. Governments should strongly intervene in the market first, gradually reducing their policy as the new business grows.The second chapter, titled “Peer effects in electric vehicle adoption,” captures the peer effect of EV adoption in Michigan, considering spatial dependence. The market competitiveness of EVs has been improved as many countries have introduced policies for stimulating EV adoption. However, a prior understanding of consumer behavior is required to achieve that goal because those policies try to alter the choices of consumers or firms in the market. Substantial literature focuses on the consumers’ substitution pattern of vehicles. The peer effect has been widely used to explain consumer behaviors, especially for products in the early stage of business. Nevertheless, there is little literature on the peer effect on EVs. Consumers may hesitate to purchase an EV at first; however, if they observe more EVs in their neighborhood, on the road, or in parking lots, their reluctance to purchase an EV may be resolved. I use spatial panel regression with EV registration and charging port panel data by ZIP Code Tabulation Area (ZCTA) from 2013 to 2019 in Lower Michigan to address the spatial dependent trend. I adopted the spatial error and autocorrelated models and compared the results with other spatial models. It shows that one increase in cumulative EV adoption at the same ZCTA will increase next year’s EV adoption by 0.326 to 0.352 cars. One cumulative EV adoption increases EV adoption in the same ZCTA by the same amount of an income increase of $1125 to $1254. The policy should be set to adopt the EV aggressively to take advantage of the peer effect, which strengthens the aggregate demand for EV adoption.The third chapter, titled “The impact of transnational municipal networks on local energy consumption,” is co-authored with Dr. Sun-Jin Yun and published in Urban Climate. Local governments are essential to the successful implementation of climate policies. They know where funds should be allocated and how to increase efficiency at the local level. Transnational municipal networks (TMNs) have galvanized local climate action by sharing best strategies and supporting communication. This study asks whether and to what extent the International Council for Local Environmental Initiatives – Local Governments for Sustainability (ICLEI), one of the major TMNs in climate action, affects local energy consumption in South Korea. We use a staggered difference-in-differences (DID) method, which is a robust alternative under staggered treatment, with a strongly balanced panel dataset across 226 Korean counties between 2005 and 2019. We find that ICLEI membership leads to a significant decrease in energy consumption per capita 4.53% to 6.62% with county membership, 8.91% to 9.00% with state membership, and 11.8% to 21.4% with both county and state membership. In addition, state membership shows a growing impact on energy consumption reduction, while county membership has a weaker trend. The results are statistical evidence of the role of TMNs in local energy policies. The central government may increase the effectiveness of its energy policy by selectively supporting ICLEI members.
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