Abstract

Climate change is an urgent issue, and 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 how much ICLEI, one of the major TMNs in climate action, affects local energy policy outcomes. We estimate the impact of ICLEI membership on energy consumption per capita using a staggered difference-in-differences (DID) method, which is a robust alternative under staggered treatment. We use 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.

JEL codes: R50, Q58, Q48, H70 

Abstract

Aggressive automobile emissions reductions are required to tackle climate change. The US government has subsidized electric vehicles (EV) to promote the transition from internal combustion engines (ICE). In this paper, we find the optimal policies and compare them: purchase and investment subsidy for EVs and investment tax for ICE. For this goal, we use dynamic programming to find how optimal policy varies over the capital accumulation of firms. In the model, firms choose price and investment, and the investment will improve the attributes and decrease the cost. With observed information and strategies, the government decides the optimal policy to maximize the social net benefits. We estimate consumer demand using annual data for every vehicle model sold in the US from 2008 to 2019. We find an equilibrium where optimal policy intervention will lead us to. In the two dynamic policies, it is the same that the optimal policy intervention is very high, as more than $15000 (EV purchase subsidy) and 40% (EV investment subsidy) at the capital level in 2019. Then, the optimal policy shrinks rapidly as EV capital increases: they reach zero when EV capital becomes 1.5 times (EV investment subsidy) and 2 times (EV purchase subsidy) EV capital in 2019. The optimal path leads us to the equilibrium where ICE capital becomes much less than half of the current capital. Regarding the total social net benefit at the equilibrium, the purchase subsidy is 2.4% higher than the current constant policy, while the investment subsidy is 1.6% less than the current one. It sheds light on the optimal intervention of governments. They should strongly intervene in the market first, gradually reducing their policy as the new business grows.

JEL codes: Q58, R48, H23, L13, L98 

Abstract

Aggressive automobile emissions reductions are required to tackle climate change. The US government has subsidized electric vehicles (EV) to promote the transition from the internal combustion engine. At the same time, the market competitiveness of EVs has improved, and many nations have introduced different types of policies for 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 codes from 2013 to 2019 in 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. 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..

JEL codes: Q58, R48