California’s Greenhouse Gas (GHG) cap-and-trade program is a key element of the suite of policies the State has adopted to achieve its climate policy goals. The passage of AB 398 (California Global Warming Solutions Act of 2006: market-based compliance mechanisms) extended the use of the cap-and-trade program for the 2021-2030 period, while also specifying modifications of the program’s “cost containment” structure and directing CARB to “[e]valuate and address concerns related to overallocation in [ARB’s] determination of the allowances available for years 2021 to 2030.” The changes being considered by CARB will not only affect the program’s stringency, but also its performance by affecting the ability of the “cost containment” structure to mitigate allowance price volatility and the risk of suddenly escalating allowance prices.
This paper analyzes the impacts of consumer subsidies in the global market for solar panels. Consumer subsidies can have at least two effects. First, subsidies shift out demand and increase equilibrium quantities, holding production costs fixed. Second, subsidies may encourage firms to innovate to reduce their costs over time. I quantify these impacts by estimating a dynamic structural model of competition among solar panel manufacturers. The model produces two key insights. First, ignoring long-run supply responses can generate biased estimates of the effects of government policy. Without accounting for induced innovation, subsidies increased global solar adoption 49 percent over the period 2010-2015, leading to over \$15 billion in external social benefits. Accounting for induced innovation increases the external benefits by at least 22 percent. Second, decentralized government intervention in a global market is inefficient. A subsidy in one country increases long-run solar adoption elsewhere because it increases investment in innovation by international firms. This spillover underscores the need for international coordination to address climate change.
I study ﬁrm behavior in new markets by examining coal-dependent private electric utili-ties’ beliefs about the sulfur dioxide allowance price following the implementation of the U.S. Acid Rain Program. The program is the ﬁrst large-scale cap-and-trade program, exposing the electric utility industry to a wholly novel market for pollution allowances. I estimate ﬁrms’ beliefs about the allowance price from 1995 to 2003 using a ﬁrm-level dynamic model of allowance trades, coal quality, and emission reduction investment. I ﬁnd that ﬁrms ini-tially underestimate the role of market fundamentals as a driver of allowance prices, but over time their beliefs appear to converge toward the stochastic process of allowance prices. Such beliefs in the ﬁrst ﬁve years of the program cost ﬁrms around 10% of their proﬁts. Beliefs also change the relative eﬃciency of cap-and-trade programs and emission taxes.
Motor vehicle fuel-economy standards have long been a cornerstone of U.S. policy to reduce fuel consumption in the light-duty vehicle fleet. In 2011 and 2012 these standards were significantly expanded in an effort to achieve steep reductions in oil demand and greenhouse gas emissions through 2025, consistent with long-term U.S. policy goals. As a policy approach, however, standards that focus on efficiency alone, as opposed to lifetime consumption, impose unnecessarily high costs and do not deliver guaranteed petroleum savings. On the basis of a commitment to cost-benefit analysis, defining U.S. regulatory policy for more than 30 years, we propose a novel policy solution that would implement a cap-and-trade system in transportation. Acknowledging that the very idea of cap and trade has become controversial, we show that this approach would increase the certainty of reductions in fuel consumption in transportation and do so at a far lower cost per gallon avoided. Such an approach is consistent with the regulatory authority existing at key federal agencies.
I estimate the water savings and property value effects of a Las Vegas area water conservation program that subsidizes conversions of lawn to desert landscape. Using event studies and panel fixed-effects models, I find that the average conversion reduces baseline water consumption by 21 percent and increases property values by about 1 percent. In addition, my results show that water savings remain relatively stable over time; that water savings are inversely proportional to annual program take-up; that participants with high pre-conversion water demand save more water than participants with lower pre-conversion water demand; and that a 6 percent price increase would have achieved equivalent savings. I find little evidence of property value spillovers to neighboring properties. The program saves water at an annual rate of \$4.84/kgal and if I include an estimate of the scarcity value of water, generates net benefits of \$2.00 per square foot of desert landscape converted.
This study explores the for labor-related production impacts of temperature stress both for its own interest and to understand the scope for adaptation to climate change. Focusing on non-agricultural output, I find that hot temperature exerts a significant causal impact on local labor product, with substantially larger effects in highly ex-posed industries such as construction, manufacturing, and transportation. Places that experience more extreme heat exposure in expectation (e.g. Houston, Orlando) exhibit lower impacts per hot day than cooler regions (e.g. Boston, San Francisco). A year with 10 additional 90°F days would reduce output per capita in highly exposed sectors by -3.5% in counties in the coldest quintile and -1.3%, roughly a third, in the warmest quintile. County-level air-conditioning penetration explains a large proportion of these differences. While these estimates suggest adaptation to heat stress in the long-run, they also imply realistic limits, at least given current technologies.
This paper postulates the conceptually useful allegory of a futuristic "World Climate Assembly" (WCA) that votes for a single worldwide price on carbon emissions via the basic democratic principle of one-person one-vote majority rule. If this WCA framework can be accepted in the first place, then voting on a single internationally-binding minimum carbon price (the proceeds from which are domestically retained) tends to counter self-interest by incentivizing countries or agents to internalize the externality. I attempt to sketch out the sense in which each WCA-agent's extra cost from a higher emissions price is counter-balanced by that agent's extra benefit from inducing all other WCA-agents to simultaneously lower their emissions in response to the higher price. The first proposition of this paper derives a relatively simple formula relating each emitter's single-peaked most-preferred world price of carbon emissions to the world "Social Cost of Carbon" (SCC). The second and third propositions relate the WCA-voted world price of carbon to the world SCC. I argue that the WCA-voted price and the SCC are unlikely to differ sharply. Some implications are discussed. The overall methodology of the paper is a mixture of mostly classical with some behavioral economics.
In this paper, I present evidence that current economics research significantly underestimates the effects of air pollution, regardless of the outcome of interest. This bias exists even in quasi-experimental estimates and arises from the way researchers define individual-level pollution exposure. A polluter’s effect on nearby residents changes dramatically with the direction of the wind, and most popular methods, including geographic diff-in-diffs and monitor-based interpolations, are unable to account for such sharp changes in exposure over short distances. To solve this problem, I use an atmospheric dispersion model, which explicitly accounts for meteorological conditions, to determine the effect of every polluting firm on every house in greater Los Angeles. I then estimate the effect of NOx emissions on house prices and neighborhood composition using the exogenous variation in emissions caused by the California Electricity Crisis of 2000 and a cap-and-trade program in greater Los Angeles. The estimated price response is much larger than past estimates and implies that the social value of the cap-and-trade program is roughly \$502 million per year, 15 times larger than the associated abatement costs. However, when based on conventional measures of pollution exposure, this estimated valuation is small and statistically indistinguishable from zero. The estimated neighborhood sorting response suggests that, despite the high aggregate value, low-income households may not have benefited much from the improvement in air quality.
Existing estimates of energy tax incidence assume that the pass-through of taxes to final consumer prices is uniform across the affected population. I show that, in fact, variation in local market conditions drives significant heterogeneity in pass-through, and ignoring this can lead to mistaken conclusions about the distributional impacts of energy taxes. I use data from the Spanish retail automotive fuel market to estimate station-specific pass-through, focusing on the effects of competition and wealth. A novel informational mandate provides access to a national, station-daily panel of retail diesel prices and characteristics and allows me to investigate market composition at a fine level. Event study and difference-in-differences regression reveal that, while retail prices rise nearly one-for-one (100%) with taxes on average, station-specific pass-through rates range from at least 70% to 115%. Greater market power – measured by brand concentration and spatial isolation – is strongly associated with higher pass-through, even after conditioning on detailed demand-side characteristics. Furthermore, pass-through rises monotonically in area-average house prices. While a conventional estimate of the Spanish diesel tax burden suggests roughly equivalent incidence across the wealth distribution, overlaying the effect of heterogeneous pass-through reveals the tax to be unambiguously progressive.
A central authority possessing tax and expenditure responsibilities can readily provide an efficient level of a public good. Absent a central authority, the case with climate change mitigation, voluntary arrangements must replace coercive arrangements; significant under-provision must be expected. Potential contributors have strong incentives to free ride, or to ride cheaply. International public goods are particularly challenging. The players - the nations of the world - are many and they start in quite different circumstances. Voluntary arrangements that might emerge from negotiations fall short for two reasons: First, players frame negotiations from their own standpoint, making stalemate likely. Second, the focal-point solution where contributions are proportional to benefits clashes with the disproportionate incentives little players have to ride cheaply. We identify a solution, the Cheap- Riding Efficient Equilibrium, which defines the relative contributions of players of differing size (or preference intensity) to reflect cheap riding incentives, yet still achieves Pareto optimality. Players start by establishing the Alliance/Nash Equilibrium as a base point. From that point they apply either the principles of the Lindahl Equilibrium or the Nash Bargaining Solution to proceed to the Pareto frontier. The former benefits from its focal-point properties; the latter is a standard analytic tool addressing bargaining. We apply our theory to climate change by first examining the Nordhaus Climate Club proposal. We then test the Alliance Equilibrium model using individual nations' Intended Nationally Determined Contributions pledged at the Paris Climate Change Conference. As hypothesized, larger nations made much larger pledges in proportion to their Gross National Incomes.
"Green Bonds" emerged as a new form of environmental financing in 2007. While most investors still view them as a niche product in the overall fixed income market, green bonds have grown rapidly to nearly \$37 billion in issuance in 2014, with issuers from the World Bank to the State of Massachusetts. This paper examines the current and potential future use of green bonds for financing sustainable land use and conservation projects around the world. The paper draws on interviews with land conservation practitioners, bond issuers, investors, and financial analysts, as well as analysis of two case studies in China and Massachusetts. The paper summarizes the key insights from this community of experts, and lays out a series of steps that will be required before green bonds can develop into a significant and reliable tool in the conservation finance toolkit. The authors find that projects linked to water and stormwater management may be investment “sweet spots” for green bonds and land conservation.
This essay provides an overview of the major emissions trading programs of the past thirty years on which significant documentation exists, and draws a number of important lessons for future applications of this environmental policy instrument. References to a larger number of other emissions trading programs that have been implemented or proposed are included.
This paper compares internationally-tradeable permits with a uniform carbon price, as seen through the lens of an individual country. To ensure a level playing field, these two approaches are initially calibrated to be welfare-equivalent for the country in a deterministic setting. While both price and quantity instruments have identical consequences under perfect certainty, outcomes differ substantially when uncertainty is introduced. The uncertainty analyzed here takes the reduced form of idiosyncratic country-specific abatement-cost shocks. Then, because of cross-border revenue flows, internationally-tradable permits can expose a country to greater risk than the imposition of a uniform carbon price (whose revenue proceeds are domestically retained). This result is formalized in a very simple model that highlights the core essence of the argument. Some implications are discussed. I suggest that this relative-riskiness result may be a pertinent consideration in choosing between negotiated price-based approaches and negotiated quantity-based approaches for controlling worldwide carbon emissions.
Perception of social rank, or how we perform relative to our peers, can be a powerful motivator. While research exists on the effect of social information on decision making, there is less work on how ranked comparisons with our peers influence our behavior. This paper outlines a field experiment conducted with 5,180 households in Castro Valley, California, which used household mailers with various forms of peer information and social rank messaging to motivate water conservation. The experiment tests the effect of a visible social rank on water use, and how the cooperative and competitive framing of rank information influences behavioral response. Difference-in-difference and matching methods reveal sizable treatment effects of the mailers on household water use (reductions of 13-17 gallons per day, depending on mailer version). However, households with relatively low or high water use in the pre-treatment period responded differently to information framing. We find that neutrally-framed rank information caused a "boomerang effect" (i.e., an increase in average water use) for low water use households, but this effect was eliminated by competitive framing. At the same time, competitively-framed rank information demotivated high water use households, increasing their average water use further. This result is supported by evidence that the competitive frame on rank information increased water use for households who ranked "last" in the peer group - a detrimental "last place effect" from competitive framing.
This paper considers the role of integrated assessment models (IAMs) in the construction of climate policy. We focus on questions involving the role of IAMs in estimating the social cost of carbon (SCC), how best to handle the considerable scientific uncertainty underlying the IAMs from the perspective of estimating the SCC, and whether an IAM‐based SCC should be abandoned and replaced by expert judgment or another substitute. The perspective we adopt in tackling these questions is rooted in the specific needs of the existing U.S. institutions responsible for making and implementing climate policy, specifically regulatory agencies within the Executive Branch and Congress should it choose to take up climate legislation. Our discussion has three premises. First, policy makers need a numerical value and an uncertainty range for the SCC for policy evaluation and implementation. Second, whatever the true value of the SCC is, it is not zero. Third, considerable uncertainty surrounds the current state of scientific knowledge about the current and future costs of climate change. The evolving nature of the science and the ultimate goal of informing first‐best policy suggests to us that the official SCC – the SCC used for regulatory analysis by the U.S. Government – should not be thought of as a single number or even a range of numbers, but more broadly as a process that yields updated estimates of those numbers and ranges. Viewed in this way, the ultimate goal of the process is scientific credibility, public acceptance, and political and legal viability.
Traditional least squares estimates of the responsiveness of gasoline consumption to changes in gasoline prices are biased toward zero, given the endogeneity of gasoline prices. A seemingly natural solution to this problem is to instrument for gasoline prices using gasoline taxes, but this approach tends to yield implausibly large price elasticities. We demonstrate that anticipatory behavior provides an important explanation for this result. We provide evidence that gasoline buyers increase gasoline purchases before tax increases and delay gasoline purchases before tax decreases. This intertemporal substitution renders the tax instrument endogenous, invalidating conventional IV analysis. We show that including suitable leads and lags in the regression restores the validity of the IV estimator, resulting in much lower and more plausible elasticity estimates. Our analysis has implications more broadly for the IV analysis of markets in which buyers may store purchases for future consumption.
In collaboration with a state environmental regulator in India, we conducted a field experiment to raise the frequency of environmental inspections to the prescribed minimum for a random set of industrial plants. The treatment was successful when judged by process measures, as treatment plants, relative to the control group, were more than twice as likely to be inspected and to be cited for violating pollution standards. Yet the treatment was weaker for more consequential outcomes: the regulator was no more likely to identify extreme polluters (i.e., plants with emissions five times the regulatory standard or more) or to impose costly penalties in the treatment group. In response to the added scrutiny, treatment plants only marginally increased compliance with standards and did not significantly reduce mean pollution emissions. To explain these results and recover the full costs of environmental regulation,we model the regulatory process as a dynamic discrete game where the regulator chooses whether to penalize and plants choose whether to abate to avoid future sanctions. We estimate this model using original data on 10,000 interactions between plants and the regulator. Our estimates imply that the costs of environmental regulation are largely reserved for extremely polluting plants. Applying the cost estimates to the experimental data, we find the average treatment inspection imposes about half the cost on plants that the average control inspection does, because the randomly assigned inspections in the treatment are less likely than normal discretionary inspections to target such extreme polluters.