Session 7: Politically Feasible Environmental and Energy Policy

The most promising path to deep decarbonization runs through the electricity sector. The goal is to reduce the carbon-intensity of the electricity sector and accelerate the electrification of other carbon-intensive sectors. This will require major investments to build a power system that is not only less carbon intensive, but also more reliable and resilient to increasingly frequent extreme weather events. How we pay for these investments will determine, to a significant extent, how much this energy transition will cost and who will bear that cost.

In practice, investments in the power system are primarily paid for by raising the price that existing customers pay for electricity. Often this implies that utilities charge volumetric (per kWh) prices far above the social marginal cost of providing an additional unit of electricity to an existing customer. This difference between price and social marginal cost amounts to a tax on electricity consumption that is used to fund the power system.

We are exploring the distributional consequences of the electricity tax and analyzing rate reforms that can improve efficiency while simultaneously advancing equity and affordability objectives. We focus in particular on California, a jurisdiction that has been pushing the pace of climate change mitigation efforts and adaptation investments in the US. The challenges manifesting in California today are likely indicative of the challenges other states will face as they try to decarbonize their electric grid, increase grid resilience, and accelerate progress on electrification.

A large literature in environmental economics has explored the efficiency and distributional properties of carbon taxation, but far less attention has been paid to the implications of electricity rate structuring. In practice, carbon pricing is playing a very small role, while investments funded through this retail electricity “tax” are high and rising. Our paper studies the efficiency and distributional implications of this increasingly important electricity tax.
 

Regulated U.S. electricity markets have transitioned away from coal capacity more slowly than restructured markets. This suggests that the current regulatory structure may be impeding transitions to new technologies. In addition, observers have alleged that regulated utilities are operating coal plants even when this is inefficient, because they are subject to a “used and useful” standard that only allows them a return on power plants that they use sufficiently. We develop and estimate a dynamic model of energy transitions in regulated electricity markets that incorporates these stylized facts. In our model, the regulator aims to provide the utility a fair rate of return on productive capital while keeping electricity rates low by limiting returns on capital when variable costs are high. In the short run, utilities make hourly operations decisions to maximize profits, given their existing capital and regulatory incentives. The regulatory structure provides two opposite operating incentives: utilities will overuse expensive coal plants to meet the used and useful standard, but this overuse will be constrained to the ex tent that it results in high variable costs. In the long run, utilities make retirement decisions for older technologies and investment decisions for new technologies. We use our model to understand how alternative regulatory structures would affect generation costs, transitions to new energy sources, and pollution. We find that eliminating the used and useful standard would decrease coal utilization in 2006 by 34 percent. By 2033, a cost-minimizing social planner would on average have 28% less coal capacity than regulated utilities under the current regulatory regime.

Building energy efficiency has been a cornerstone of greenhouse gas mitigation strategies for decades. However, impact evaluations have revealed that energy savings typically fall short of engineering model forecasts that currently guide funding decisions. This creates a resource allocation problem that impedes progress on climate change. Using data from the largest U.S. energy efficiency program, we demonstrate that a data-driven approach to predicting retrofit impacts based on previously realized outcomes is more accurate than the status quo engineering models. Targeting high-return interventions based on these predictions dramatically increases net social benefits, from $0.93 to $1.23 per dollar invested.

 We develop a framework for maximizing the net benefits of phaseout programs designed to reduce externalities, focusing on the special case of programs that involve the scheduled retirement of coal-fired electric power plants. These programs are second-best policies, but may have the potential to lead to large welfare gains given their revealed political acceptability and the urgency of addressing climate change. We identify that the core policy problem is one of identifying assetand time-specific net benefits of retirement and scheduling retirement to maximize program net benefits. We apply the framework to design a program that would have phased out coal-fired electricity generation in the state of New York between 2008 and 2017 and model electricity market production and wholesale price adjustments. We find that a coal phaseout program would have led to between $193 and $269 million in gains from the reduction of external (climate) damages during this time, depending on assumptions about entry of alternative assets. We characterize changes in producer surplus that are experienced by coal and natural gas plant owners from the program, through a reallocation of electricity generator production and wholesale price adjustments.

Trade policy is often cast as a solution to the free-riding problem in international climate agreements. This paper uncovers the extent to which trade policy can deliver on this promise. We introduce abatement technology and carbon externality into a multi-country, multi-industry quantitative trade model. Our framework accommodates a rich set of policy considerations, including firm delocation, multilateral carbon leakage, and returns to scale in production and abatement. By deriving simple analytical formulas for optimal carbon, production, and border taxes, we are able to quantify the reduction in CO2 emissions under two prominent proposals that combine carbon pricing with trade policy.

First, we show that carbon border taxes can replicate at most 1% of the CO2 reduction attainable under global climate cooperation. By comparison, Nordhaus's (2015) climate club proposal can foster global climate cooperation and reduce global CO2 emissions by up to 61%. This successful outcome hinges on both the US and EU committing to the climate club as core members, using their collective trade penalties to enforce climate cooperation by reluctant governments.

The rapid decline in the global cost of solar panels coincided with China’s growing market dominance in the solar PV from the early 2000s. We evaluate the effectiveness of local policy efforts to encourage the growth of the solar industry across Chinese cities. We develop novel measures covering all policies since their inception based on text analysis; construct original data on patenting, production, and trade; and implement a synthetic-difference-in-difference approach.

We show that city-level subsidies for solar production cause large increases in solar PV output (measured in MegaWatts per Hour), but (with a lag) also raise solar innovation and productivity relative to matched control cities that did not implement such policies. Cities who combined these production subsidies with RD support had even larger positive effects. We also document positive impacts on solar firm numbers, revenues, and exports. Demand and installation subsidies, by contrast, have no significant local impact on these outcomes, which we argue is because demand can be supplied from other locations.

These results are consistent with the predictions of a model in which electricity is supplied locally using components (solar panels) sourced from heterogeneous firms across China (subject to transport costs), who endogenously chose whether to pay the fixed costs of exporting and/or innovation. There is no evidence of negative business stealing effects on neighboring cities. Taken together, these results suggest that industrial policy can foster growth and innovation, which is the central tenet of industrial policy that underlies policies elsewhere such as the US Inflation Reduction Act and European Green Deal. The fact that we observe this in an industry that is displacing dirty energy generation worldwide magnifies the importance of our findings.

Conventional wisdom claims that renewables and storage are complements. However, we show that this relationship does not always hold. In markets where renewables availability moves procyclically in relation to demand and renewable capacity is small, increasing storage (renewable) capacity negatively impacts renewable (storage) firms and total welfare. The same applies to the "scarce" renewable technology in multi-technology markets with both procyclical and countercyclical technologies. These findings have policy implications for the optimal timing and effectiveness of mandates or subsidies for renewables and storage. Simulations of the Spanish wholesale electricity market illustrate our results.

The Inflation Reduction Act (IRA) represents the largest federal response to climate change to date. We highlight the key climate provisions and assess the Act’s potential economic impacts. Substantially higher investments in clean energy and electric vehicles imply that fiscal costs may be larger than projected. However, even at the high end, IRA provisions remain cost-effective. IRA has large impacts on power sector investments and electricity prices, lowering retail electricity rates and resulting in negative prices in some wholesale markets. We find small quantitative macroeconomic effects including a small decline in headline inflation, but macroeconomic conditions – particularly higher interest rates and materials costs – may have substantial negative effects on clean energy investment. We show that the subsidy approach in IRA has expansionary supply-side effects relative to a carbon tax but, in a representative-agent dynamic model, is preferable to a carbon tax only in the presence of a strong learning-by-doing externality. We also discuss the economics of the industrial policy aspects of the act as well as the distributional impacts and the possible incidence of the different tax credits in IRA.

When pricing and product entry decisions are made nationally but policy varies by state, subsidies and taxes levied on producers are no longer equivalent to those levied on consumers due to cross-state spillovers. We study an important state-level environmental mandate in the early electric vehicle industry: the Zero-Emission Vehicle (ZEV) policy in California and nine other states. Focusing on the 2009–17 period, we examine the effects of the mandate on firm pricing and electric vehicle product entry in both ZEV and non-ZEV states.

Using a structural model of the market for new vehicles, including nationally-set prices, state-level consumer demand, and endogenous electric vehicle entry, we compare the mandate to a counterfactual demand-side policy that instead uses a consumer subsidy and tax. Holding fixed total electric vehicle sales in regulated states, the demand-side policy has heterogeneous effects on prices, creates a weaker incentive for socially beneficial product entry, and generates lower consumer and total surplus.

The global battery industry has achieved significant cost savings: electric vehicle (EV) battery costs have dropped by more than 90% over the past decade. This study assesses the extent to which this sharp decline in lithium-ion battery prices is attributable to learning-by-doing in battery production, and quantifies the impact of two types of government policies (e.g., consumer subsidies and domestic content requirement) on learning, technology diffusion, and industry dynamics.

Our analysis is based on rich data consisting of model-level sales, prices, and attributes of EVs for 13 top EV countries, and information on battery suppliers and characteristics. We estimate a structural model of the global EV industry, accounting for consumer vehicle choices, EV makers’ pricing decisions, and bilateral bargaining between EV manufacturers and battery suppliers over battery prices. We recover the model-implied battery costs and evaluate how battery costs change with the accumulated production experience of battery suppliers. The identification of learning-by-doing in battery production relies on variations in EV consumer subsidies across vehicle models as well variations in battery supply networks due to domestic content requirements.

Our estimates suggest a learning rate of 18% and that learning-by-doing explained a substantial portion of the observed battery cost reductions. Learning-by-doing greatly magnified the impact of EV consumer subsidies on adoption, suggesting that the existing estimates from the literature drastically under-estimated the sales impact of consumer subsidies. We then conduct simulations to examine the impacts of domestic content requirement, a strategy adopted by China and more recently the US., on market share dynamics and global EV adoption. Our results suggest that China’s whitelist policy nearly doubled the market share of Chinese battery suppliers mostly at the expense of South Korean suppliers.

We develop a new measure of impact elasticity, defined as a firm’s change in environmental impact due to a change in its cost of capital. We show empirically that a reduction in financing costs for firms that are already green leads to small improvements in impact at best. In contrast, increasing financing costs for brown firms leads to large negative changes in firm impact. Thus, sustainable investing that directs capital away from brown firms and toward green firms may be counterproductive, in that it makes brown firms more brown without making green firms more green.

We further show that brown firms face very weak incentives to become more green. Due to a mistaken focus on percentage reductions in emissions, the sustainable investing movement primarily rewards green firms for economically trivial reductions in their already low levels of emissions.

Forests accompany the cities we build. There are an estimated 5.5 billion urban trees in the United States. Globally, about 25 percent of urban land is covered by tree canopy. This study examines urban forests as a policy tool for air pollution mitigation. We study an afforestation program in the city of Beijing, which planted a total of 2 million mu of greenery – roughly the size of Los Angeles – across the city over a decade.

We conduct a remote-sensing audit of the program, finding that it contributes to a substantial greening up of the city. This causes significant downwind air quality improvement, reducing the average PM2.5 concentration at city population hubs by 4.2 percent. Rapid vegetation growth, however, led to a 7.4 percent increase in pollen exposure. Analysis of medical claims data shows aeroallergens triggered emergency room visits, mirroring well-documented industrial pollution effects though less severe.

We offer insight on managing urban forests’ health risks, identifying harmful pollen species and susceptible population subgroups.

This project analyzes how a principal can motivate an agent to conserve rather than exploit a depletable resource. This dynamic problem is relevant for tropical deforestation as well as for other environmental problems. It is shown that the smaller is the agent's discount factor (e.g., because of political instability), the more the principal benefits from debt-for-nature contracts compared to flow payments (in return for lower deforestation). The debt-for-nature contract combines a loan to the agent with repayments that are contingent on the forest cover.

This paper applies principles of adverse selection to overcome obstacles that prevent the implementation of Pigouvian policies to internalize externalities. Focusing on negative externalities from production (such as pollution), we consider settings in which aggregate emissions are known, but individual contributions are unobserved by the government. We evaluate a policy that gives firms the option to pay a tax on their voluntarily and verifiably disclosed emissions, or pay an output tax based on the average rate of emissions among the undisclosed firms. The certification of relatively clean firms raises the output-based tax, setting off a process of unraveling in favor of disclosure.

We derive sufficient statistics formulas to calculate the welfare of such a program relative to mandatory output or emissions taxes. We find that the voluntary certification mechanism would deliver significant gains over output-based taxation in two empirical applications: methane emissions from oil and gas fields, and carbon emissions from imported steel.

International climate policy negotiations have focused on mitigating climate change through reduced emissions and on adapting to ongoing and future climate change. Progress on mitigation has been debatable, as the international community has produced few binding commitments to reduce emissions. Fortunately, progress on adaptation has been much more tangible, with established adaptation funds and promises of future funding. Publicly-funded adaptation is currently over $50 billion per year, doubling since 2015 (Climate Policy Initiative, 2021), and funding needs are expected to grow to $340 billion by 2030 and $550 billion by 2050 (UNEP, 2022).1 Adaptation funds have focused on protecting “particularly vulnerable” populations from climate change (Chen et al., 2018). This objective is especially important because climate change may increase economic inequality (e.g., Dell et al., 2012; Diffenbaugh and Burke, 2019; Palagi et al., 2022). Despite the scale of the adaptation challenge, there has been little formal guidance regarding how adaptation funds can most effectively protect vulnerable populations and  prevent climate change from increasing inequality, which may be a reason why adaptation funds have in practice simply tried to distribute funding equally  across a set of countries without much regard for their relative vulnerability (Persson and Remling, 2014; Remling and Persson, 2015).

I build an empirical model of the South American agricultural sector to show how environmental policy is transmitted along a supply chain when regulation at the externality’s source is infeasible. Given obstacles to a carbon tax on farmers, I show how alternative market-based policies—downstream agribusiness taxes—reduce upstream emissions but their effectiveness is limited by international leakage and domestic mistargeting, while also being regressive. Agribusiness monopsony power worsens targeting by lowering pass-through to upstream farmers in uncompetitive and emissions-intense regions, thus eroding the Pigouvian signal where the social cost is highest. By contrast, command-and-control tools perform robustly when markets face pre-existing distortions.

Trade policy is often cast as a solution to the free-riding problem in international climate agreements. This paper uncovers the extent to which trade policy can deliver on this promise. We introduce abatement technology and carbon externality into a multi-country, multi-industry quantitative trade model. Our framework accommodates a rich set of policy considerations, including firm delocation, multilateral carbon leakage, and returns to scale in production and abatement. By deriving simple analytical formulas for optimal carbon, production, and border taxes, we are able to quantify the reduction in CO2 emissions under two prominent proposals that combine carbon pricing with trade policy.

First, we show that carbon border taxes can replicate at most 1% of the CO2 reduction attainable under global climate cooperation. By comparison, Nordhaus's (2015) climate club proposal can foster global climate cooperation and reduce global CO2 emissions by up to 61%. This successful outcome hinges on both the US and EU committing to the climate club as core members, using their collective trade penalties to enforce climate cooperation by reluctant governments.

How does multinational production affect climate change? Global climate negotiations have set the goal of enormous transfers per year from rich to poor countries, including through private investment, to address climate change. Two stylized facts motivate the analysis of multinational production as a mechanism for such transfers. First, carbon emissions per dollar of value added or output differ substantially across countries, even conditional on industrial composition. Second, the emissions rate of a foreign-owned plant increases with the emission rate of its home country, suggesting that firms bring green technology with them when operating abroad.

We develop and quantify a multi-country general equilibrium model of multinational production, trade, and energy to assess how policies encouraging multinational production would affect global carbon emissions and welfare.