A Welfare Analysis of Policies Impacting Climate Change

This paper extends and applies the marginal value of public funds (MVPF) framework to evaluate the welfare consequences of 96 climate-related tax and spending policies in the United States. The MVPF is a benefit-cost ratio in which the numerator captures all benefits to individuals (measured by their willingness to pay) and the denominator captures net government costs; policies with higher MVPFs are better spending policies, while those with lower MVPFs are more efficient revenue-raising instruments.

The sample covers policies rigorously evaluated using quasi-experimental or experimental methods drawn from 18 major economics journals between January 1999 and December 2023. Policies fall into three primary categories: subsidies (wind production tax credits, residential solar, electric vehicles, hybrid vehicles, vehicle buybacks, appliance rebates, and weatherization), nudges and marketing, and revenue raisers (gasoline taxes, other fuel taxes, cap-and-trade). A selected set of international aid policies is also analyzed. The analysis applies a harmonized method for translating behavioral changes into emissions changes — using the EPA’s AVERT model for electricity-sector emissions — and a consistent set of externality valuations, including an EPA 2023 social cost of carbon (SCC) of $193 per ton of CO2 in 2020 (rising over time), with robustness checks at $76, $337, and $1,367.

The primary methodological contribution is a new sufficient statistics approach to quantifying learning-by-doing (LBD) externalities. When marginal cost of production is an isoelastic function of cumulative production and demand is an isoelastic function of price, the time path of production satisfies a second-order ordinary differential equation whose solution yields society’s willingness to pay for LBD spillovers. LBD generates two types of externalities: a price externality (lower future consumer prices) and an environmental externality (increased future take-up of clean goods). The approach requires four inputs: price elasticity of demand, elasticity of marginal cost with respect to cumulative production, cumulative production at the time of the subsidy, and product cost at the time of the subsidy.

The three main empirical findings are as follows. First, subsidies for production that directly displaces dirty electricity generation have the highest MVPFs. Wind production tax credits have an MVPF of 3.85 without LBD, rising to 5.87 with LBD. Residential solar subsidies have an MVPF of 1.45 without LBD, rising to 3.86 with LBD. EV subsidies have an MVPF of approximately 1.4 with LBD and approximately 1 without it. Consumer subsidies for appliances, weatherization, vehicle retirement, and hybrid vehicles have MVPFs around 1. Second, conservation nudges targeting electricity consumption can deliver MVPFs exceeding 5 in regions with relatively dirty electric grids, but fall below 1 in cleaner-grid regions such as California and the Northeast — and their effectiveness is expected to decline as grids decarbonize. Third, fuel taxes (gasoline, diesel, jet fuel) and cap-and-trade permit reductions are efficient revenue raisers, with nearly all having MVPFs below 1 and most below 0.7, reflecting the Pigouvian logic that current tax rates fall below the associated environmental externalities. Cap-and-trade permit reductions can produce MVPFs below zero, meaning revenue is raised while providing net positive welfare to individuals.

The paper also constructs three cost-per-ton metrics — resource cost per ton, government cost per ton, and social cost per ton — and shows they can yield substantively different and sometimes opposite rankings relative to each other and to the MVPF. For example, EV subsidies carry a government cost per ton of $1,356 (among the highest in the sample) yet an MVPF above most consumer subsidies, because that metric omits non-CO2 benefits including LBD effects. The scope of the analysis is US historical policy, with the MVPF comparison most informative when social welfare weights across beneficiary groups are treated as roughly equal.

Q: What is the MVPF framework and how does it differ from cost-per-ton analysis? A: The MVPF equals benefits to individuals (sum of willingness to pay) divided by net cost to the government. It is designed for a decision-maker maximizing social welfare subject to a budget constraint, whereas cost-per-ton metrics serve a decision-maker minimizing cost subject to a fixed CO2 reduction target. A higher MVPF means more welfare gain per dollar spent; a lower MVPF means less welfare cost per dollar of revenue raised.

Q: What are the three cost-per-ton definitions the paper distinguishes, and why do they differ? A: Resource cost per ton measures the economic resources consumed per ton of CO2 abated, independent of subsidy incidence; government cost per ton measures net government outlays per ton, omitting all non-CO2 benefits; social cost per ton subtracts non-CO2 benefits from government costs. For appliance rebates, these three values are -$2, $474, and an intermediate figure — a range that reflects whether inframarginal transfers and non-CO2 co-benefits are counted.

Q: What is the new methodological contribution regarding learning by doing? A: The paper derives a sufficient statistics result showing that when marginal production cost is an isoelastic function of cumulative production and demand is isoelastic in price, the time path of production follows a second-order ordinary differential equation. Solving this equation yields society’s willingness to pay for LBD spillovers from four observable parameters: demand price elasticity, the LBD elasticity of marginal cost with respect to cumulative production, cumulative production at the subsidy date, and unit cost at that date. This allows LBD benefits to be incorporated into both MVPF and cost-per-ton calculations without requiring a fully calibrated dynamic model.

Q: What LBD elasticities does the paper use, and where do they come from? A: Drawing on Way et al. (2022), a 1% increase in cumulative solar production is associated with a 0.319% price reduction; for wind the elasticity is 0.194%, and for EV batteries it is 0.421%. These are treated as the isoelastic parameter in the sufficient statistics formula.

Q: How does LBD affect the MVPF estimates for wind, solar, and EVs specifically? A: For wind production tax credits, the MVPF rises from 3.85 to 5.87 when LBD is included. For residential solar, it rises from 1.45 to 3.86. For EV subsidies, the MVPF rises from approximately 1 to approximately 1.4. Without LBD, EV subsidies are in line with other consumer subsidies; LBD is the primary reason EVs outperform that group.

Q: What is the baseline social cost of carbon used, and how sensitive are results to alternative values? A: The baseline SCC is $193 per ton of CO2 in 2020, following EPA 2023 guidance at a 2% discount rate. Robustness checks use $76, $337, and $1,367. Higher SCC values raise the MVPF of all subsidies in the sample, but the relative ordering — with wind PTCs above all other consumer subsidies — remains consistent across the full range.

Q: How are EV subsidies evaluated, and what accounts for their MVPF exceeding other consumer subsidies? A: The analysis uses the California EFMP program studied by Muehlegger and Rapson (2022), which finds a price elasticity of demand of -2.1 and 85% pass-through to consumers (15% captured by dealers). A $1 subsidy generates $0.85 in consumer WTP, $0.15 in dealer WTP, $0.17 in CO2 co-benefits, $0.05 in local pollution and accident co-benefits, offset by $0.10 in damages from increased electricity generation. Most benefits are non-environmental (inframarginal transfers and LBD effects on future vehicle prices), which is why the government cost per ton of $1,356 appears high while the MVPF is approximately 1.4.

Q: What drives the high MVPFs for nudges in dirty-grid regions, and what is the implication for the future? A: Conservation nudges in dirty-grid areas have high MVPFs (exceeding 5) because each kilowatt-hour of reduced consumption displaces generation from high-emission sources, amplifying the environmental benefit per dollar of program cost. In cleaner-grid regions like California and the Northeast, the same nudge displaces lower-emission generation, pushing the MVPF below 1. As grids decarbonize nationwide, the paper notes that nudge MVPFs will decline over time.

Q: How do cap-and-trade permit reductions compare to fuel taxes as revenue-raising instruments? A: Nearly all fuel taxes (gasoline, diesel, jet fuel) have MVPFs below 1, with most below 0.7, meaning they impose a welfare cost of only $0.70 per dollar of revenue raised. Cap-and-trade permit reductions can have MVPFs below zero, meaning they can raise revenue while simultaneously providing net positive welfare gains to individuals because environmental benefits from reduced emissions outweigh the permit costs borne by emitters.

Q: What do the international subsidy findings suggest, and what are their limitations? A: Subsidies for efficient charcoal cookstoves in Kenya (Berkouwer and Dean 2022) generate US-specific gains from CO2 reductions that are 37 times the net cost of the subsidy; including global benefits raises the MVPF to 323. However, the paper flags substantial uncertainty: estimated policy impacts vary widely within similar international categories, and the US-specific MVPF is highly sensitive to assumptions about the incidence of the social cost of carbon on US residents and US government tax revenue.

Q: Why does the social cost per ton metric give opposite rankings within wind, solar, and EVs relative to the MVPF? A: EVs have a social cost per ton of -$415 versus -$32 for wind PTCs, making EVs appear superior on that metric — the reverse of the MVPF ordering. The paper explains that when SCPT values are negative (policies that abate CO2 while also yielding positive non-CO2 net benefits), the metric loses its Lagrange multiplier interpretation: increased non-CO2 benefits make SCPT more negative while increased abatement makes it less negative, preventing meaningful cross-policy comparisons.

Q: What is the overall policy ranking implied by the MVPF analysis? A: From highest to lowest MVPF: international clean energy subsidies > wind production tax credits > residential solar subsidies > energy conservation nudges (dirty grids) > EV subsidies > consumer appliance and weatherization subsidies > hybrid vehicle subsidies > vehicle buyback rebates > energy conservation nudges (clean grids) > revenue raisers (gas taxes, fuel taxes, cap-and-trade). The paper notes that shifting $1 of government revenue from gas taxes (MVPF ~0.67) to wind PTCs (MVPF ~5.87) generates $5.20 in net welfare benefits to individuals, assuming equal social welfare weights across groups.

Marginal Value of Public Funds (MVPF): A benefit-cost ratio equal to the sum of individuals’ willingness to pay for a policy divided by its net cost to the government. Policies with higher MVPFs deliver greater welfare gains per dollar spent; those with lower MVPFs impose lower welfare costs per dollar of revenue raised. Used to compare spending and revenue-raising policies on a common welfare-maximizing basis.

Learning-by-Doing (LBD) Externality: The spillover by which current production of a technology lowers its future marginal cost, generating future consumer surplus (price externality) and additional future uptake with associated environmental benefits (environmental externality). Treated in this paper as an uninternalized external benefit of subsidizing current production.

Sufficient Statistics Approach to LBD: The paper’s methodological contribution — showing that when marginal cost is an isoelastic function of cumulative production and demand is isoelastic in price, the LBD welfare benefit can be computed from four observables: the demand price elasticity, the LBD cost elasticity, cumulative production at subsidy date, and unit cost at subsidy date, without requiring a fully specified dynamic model.

Resource Cost per Ton (RCPT): Economic resources consumed to produce and use a product, divided by tons of CO2 abated. Appropriate for private firms minimizing abatement cost; independent of subsidy take-up rates and inframarginal transfers.

Government Cost per Ton (GCPT): Net government outlay per ton of CO2 abated. The correct metric for a government focused exclusively on CO2 reduction at minimum fiscal cost; omits all non-CO2 welfare impacts, including co-benefits and LBD effects.

Social Cost per Ton (SCPT): Government cost net of all non-CO2 benefits, per ton of CO2 abated. Intended to capture the social cost of abatement, but loses its Lagrange multiplier interpretation when values are negative, preventing valid cross-policy comparisons in that region.

Social Cost of Carbon (SCC): The monetized damage from one additional ton of CO2 emissions. Baseline value of $193 per ton in 2020 from EPA 2023 at a 2% discount rate, rising over time. A key parameter driving MVPF levels across all policy categories; robustness checked at $76, $337, and $1,367.

Pigouvian Efficiency of Environmental Taxes: The paper quantifies that fuel taxes have MVPFs below 0.7 because current tax rates fall below the associated Pigouvian optimum — i.e., taxing polluting goods raises revenue while reducing a pre-existing negative externality, so the welfare cost of the revenue is less than one dollar per dollar raised.