Associate Professor and Director of Graduate Studies, Department of Economics, University of Arizona
Research Associate, National Bureau of Economic Research
Associate Fellow, Centre for Economic Policy Research
From Jan 2023: Co-editor, Journal of the Association of Environmental and Resource Economists
Accepted or Conditionally Accepted:
Unpublished working papers:
Estimating the Consequences of Climate Change from Variation in Weather (free version, VoxEU post) (updated May 2021)
(for earlier applied policy working paper, see Incentivizing Negative Emissions Through Carbon Shares, free version, VoxEU post)
Rationally Misplaced Confidence (updated October 2021, with new proofs for exponential families)
What Were the Odds? Estimating the Market's Probability of Uncertain Events (with Ashley Langer)
In progress, late-stage:
Financial Markets Value Skillful Forecasts of Seasonal Climate (with Sarah Kapnick)
Fatal Errors: The Mortality Value of Accurate Weather Forecasts (with Laura Bakkensen and Jeff Shrader)
Energy and Economic Growth
Hedging Climate Risk
Arctic Monitoring (with a few coauthors)
Designing Adaptation Portfolios in a Networked Economy (with I. Rudik and W. Tan)
Primary Peer-Reviewed Publications
Langer, A. and D. Lemoine. 2022. Journal of the Association of Environmental and Resource Economists 9(6):1197-1234. doi: 10.1086/719949
We analyze the efficient subsidy for durable good technologies. We theoretically demonstrate that a policy maker faces a tension between intertemporally price discriminating by designing a subsidy that increases over time and taking advantage of future technological progress by designing a subsidy that decreases over time. Using dynamic estimates of household preferences for residential solar in California, we show that the efficient subsidy increases over time. The regulator’s spending quintuples when households anticipate future technological progress and future subsidies.
Lemoine, D. 2021. Journal of the Association of Environmental and Resource Economists 8(1):27-57. doi: 10.1086/710667
I analyze the marginal value of reducing greenhouse gas emissions (the “social cost of carbon”) under uncertainty about warming, under uncertainty about how much warming reduces consumption, and under stochastic shocks to consumption growth. I theoretically demonstrate that each of these sources of uncertainty increases the social cost of carbon under conventional preferences. In a calibrated numerical implementation, uncertainty increases the 200-year social cost of carbon by more than 20%. Uncertainty about the consumption impacts of warming contributes the most to this premium and makes the social cost of carbon sensitive to impacts even after 2400.
Lemoine, D. 2020. European Economic Review 125:103431. doi: 10.1016/j.euroecorev.2020.103431
Energy efficiency improvements "rebound" when economic responses undercut their direct energy savings. I show that general equilibrium channels typically amplify rebound by making consumption goods cheaper but typically dampen rebound by increasing demand for non-energy inputs to production and by changing the size of the energy supply sector. Improvements in the efficiency of the energy supply sector generate especially large rebound because they make energy cheaper in all other sectors. Quantitatively, general equilibrium channels reduce rebound in U.S. consumption good sectors from 39% to 28% but increase rebound in the energy supply sector from 42% to 80%.
Lemoine, D. 2018. Journal of Economic Behavior and Organization 153:143-152. doi:10.1016/j.jebo.2018.07.002
Our perception of time is both nonlinear and nonstationary, which makes preference reversals possible. I decompose the sources of dynamic inconsistency into a time acceleration effect and a time compression effect. Standard economic models focus only on the second effect. I show that when the perceived flow of time accelerates with age, the two effects can offset each other for hyperbolic discounters but not for exponential discounters. Such hyperbolic discounters would report discount rates that seem to imply dynamic inconsistency but would nonetheless manifest dynamic consistency in actual choices over time.
Lemoine, D. and I. Rudik. 2017. American Economic Review 107(10):2947-57. doi: 10.1257/aer.20150986
Common views hold that the efficient way to limit warming to a chosen level is to price carbon emissions at a rate that increases exponentially. We show that this "Hotelling" tax on carbon emissions is actually inefficient. The least-cost policy path takes advantage of the climate system's inertia to delay reducing emissions and allow greater cumulative emissions. The efficient carbon tax follows an inverse-U-shaped path and grows more slowly than the Hotelling tax. Economic models that assume exponentially increasing carbon taxes are overestimating the cost of limiting warming, overestimating the efficient near-term carbon tax, and overvaluing technologies that mature sooner.
Green Expectations: Current Effects of Anticipated Carbon Pricing (pdf, copyright MIT Press)
Lemoine, D. 2017. Review of Economics and Statistics 99(3):499-513. doi: 10.1162/REST_a_00627
I report evidence that an anticipated strengthening of environmental policy increased emissions. I find that the breakdown of the U.S. Senate's 2010 climate effort generated positive excess returns in coal futures markets. This response appears to be driven by an increase in coal storage. The proposed legislation aimed to reduce U.S. greenhouse gas emissions after 2013, but the legislative process itself may have increased emissions by over 12 million tons of carbon dioxide leading up to April 2010.
Lemoine, D. and I. Rudik. 2017. Annual Review of Resource Economics 9:117-142. doi: 10.1146/annurev-resource-100516-053516
Uncertainty is critical to questions about climate change policy. Recently developed recursive integrated assessment models have become the primary tools for studying and quantifying the policy implications of uncertainty. We decompose the channels through which uncertainty affects policy and quantify them in a recursive extension of a benchmark integrated assessment model. The first wave of recursive models has made valuable, pioneering efforts at analyzing disparate sources of uncertainty. We argue that frontier numerical methods will enable the next generation of recursive models to better capture the information structure of climate change and to thereby ask new types of questions about climate change policy.
Lemoine, D. 2017. Environmental and Resource Economics 67(4):789-821. doi: 10.1007/s10640-016-0006-6
An increasingly common type of environmental policy instrument regulates the carbon intensity of transportation and electricity markets. In order to extend the policy's scope beyond point-of-use emissions, regulators assign each potential fuel an emission intensity rating for use in calculating compliance. I show that welfare-maximizing ratings do not generally coincide with the best estimates of actual emissions. In fact, the regulator can achieve a higher level of welfare by properly selecting the emission ratings than possible by selecting only the level of the standard. Moreover, a fuel's optimal rating can actually decrease when its estimated emission intensity increases. Numerical simulations of the California Low-Carbon Fuel Standard suggest that when recent scientific information increased the estimated emissions from conventional ethanol, regulators should have lowered ethanol's rating (making it appear less emission-intensive) so that the fuel market would clear with a lower quantity.
Lemoine, D. and C.P. Traeger. 2016. Nature Climate Change 6(5):514-519.doi:10.1038/nclimate2902
Greenhouse gas emissions can trigger irreversible regime shifts in the climate system, known as tipping points. Multiple tipping points affect each other’s probability of occurrence, potentially causing a ‘domino effect’. We analyse climate policy in the presence of a potential domino effect. We incorporate three different tipping points occurring at unknown thresholds into an integrated climate–economy model. The optimal emission policy considers all possible thresholds and the resulting interactions between tipping points, economic activity, and policy responses into the indefinite future. We quantify the cost of delaying optimal emission controls in the presence of uncertain tipping points and also the benefit of detecting when individual tipping points have been triggered. We show that the presence of these tipping points nearly doubles today’s optimal carbon tax and reduces peak warming along the optimal path by approximately 1 °C. The presence of these tipping points increases the cost of delaying optimal policy until mid-century by nearly 150%.
Lemoine, D. and S. Kapnick. 2016. Nature Climate Change 6(1):51-55. doi:10.1038/nclimate2759
To evaluate policies to reduce greenhouse-gas emissions, economic models require estimates of how future climate change will affect well-being. So far, nearly all estimates of the economic impacts of future warming have been developed by combining estimates of impacts in individual sectors of the economy. Recent work has used variation in warming over time and space to produce top-down estimates of how past climate and weather shocks have affected economic output. Here we propose a statistical framework for converting these top-down estimates of past economic costs of regional warming into projections of the economic cost of future global warming. Combining the latest physical climate models, socioeconomic projections, and economic estimates of past impacts, we find that future warming could raise the expected rate of economic growth in richer countries, reduce the expected rate of economic growth in poorer countries, and increase the variability of growth by increasing the climate’s variability. This study suggests we should rethink the focus on global impacts and the use of deterministic frameworks for modelling impacts and policy. Press Releases: UA News, NOAA
Lemoine, D. and C.P. Traeger. 2016. Journal of Economic Behavior & Organization 132:5-18. doi:10.1016/j.jebo.2016.03.009
We analyze the policy implications of aversion to Knightian uncertainty (ambiguity) about the possibility of tipping points. We demonstrate two channels through which uncertainty aversion affects optimal policy in the general setting. The first channel relates to the policy's effect on the probability of tipping, and the second channel to its differential impact in the pre- and post-tipping regimes. We then extend a recursive dynamic model of climate policy and tipping points to include uncertainty aversion. Numerically, aversion to Knightian uncertainty in the face of an ambiguous tipping point increases the optimal tax on carbon dioxide emissions, but only by a small amount.
Lemoine, D. and C. Traeger. 2014. American Economic Journal: Economic Policy 6(1):137-166. doi:10.1257/pol.6.1.137
We investigate the optimal policy response to the possibility of abrupt, irreversible shifts in system dynamics. The welfare cost of a tipping point emerges from the policymaker's response to altered system dynamics. Our policymaker also learns about a threshold's location by observing the system's response in each period. Simulations with a recursive, numerical climate-economy model show that tipping possibilities raise the optimal carbon tax more strongly over time. The resulting policy paths ultimately lower optimal peak warming by up to 0.5 degrees C. Different types of post-tipping shifts in dynamics generate qualitatively different optimal pre-tipping policy paths.
Baker, E., M. Fowlie, D. Lemoine, and S.S. Reynolds. 2013. Annual Review of Resource Economics 5(1):387-426. doi:10.1146/annurev-resource-091912-151843
The benefits and costs of increasing solar electricity generation depend on the scale of the increase and on the timeframe over which it occurs. Short-run analyses focus on the cost-effectiveness of incremental increases in solar capacity, holding the rest of the power system fixed. Solar's variability adds value if its power occurs at high-demand times and displaces relatively carbon-intensive generation. Medium-run analyses consider the implications of non-incremental changes in solar capacity. The cost of each installation may fall through experience effects, but the cost of grid integration increases when solar requires ancillary services and fails to displace investment in other types of generation. Long-run analyses consider the role of solar in reaching twenty-first century carbon targets. Solar's contribution depends on the representation of grid integration costs, on the availability of other low-carbon technologies, and on the potential for technological advances. By surveying analyses for different time horizons, this paper begins to connect and integrate a fairly disjointed literature on the economics of solar energy.
Lemoine, D. and H.C. McJeon. 2013. Environmental Research Letters 8:034019. doi:10.1088/1748-9326/8/3/034019
Climate change policies must trade off uncertainties about future warming, about the social and ecological impacts of warming, and about the cost of reducing greenhouse gas emissions. We show that laxer carbon targets produce broader distributions for climate damages, skewed towards severe outcomes. However, if potential low-carbon technologies fill overlapping niches, then more stringent carbon targets produce broader distributions for the cost of reducing emissions, skewed towards high-cost outcomes. We use the technology-rich GCAM integrated assessment model to assess the robustness of 450 ppm and 500 ppm carbon targets to each uncertain factor. The 500 ppm target provides net benefits across a broad range of futures. The 450 ppm target provides net benefits only when impacts are greater than conventionally assumed, when multiple technological breakthroughs lower the cost of abatement, or when evaluated with a low discount rate. Policy evaluations are more sensitive to uncertainty about abatement technology and impacts than to uncertainty about warming.
Lemoine, D.M. 2010. Journal of Climate 23(16):4395-4415. doi:10.1175/2010JCLI3503.1
Uncertainty about biases common across models and about unknown and unmodeled feedbacks is important for the tails of temperature change distributions and thus for climate risk assessments. This paper develops a hierarchical Bayes framework that explicitly represents these and other sources of uncertainty. It then uses models' estimates of albedo, carbon cycle, cloud, and water vapor-lapse rate feedbacks to generate posterior probability distributions for feedback strength and equilibrium temperature change. The posterior distributions are especially sensitive to prior beliefs about models' shared structural biases: nonzero probability of shared bias moves some probability mass towards lower values for climate sensitivity even as it thickens the distribution's positive tail. Obtaining additional models of these feedbacks would not constrain the posterior distributions as much as would narrowing prior beliefs about shared biases or, potentially, obtaining feedback estimates having biases uncorrelated with those impacting climate models. Carbon dioxide concentrations may need to fall below current levels in order to maintain only a 10% chance of exceeding official 2 degrees Celsius limits on global average temperature change.
Lemoine, D.M. 2010. Journal of Geophysical Research 115:D22122. doi:10.1029/2010JD014725
If climate-carbon feedbacks are positive, then warming causes changes in carbon dioxide (CO2) sources and sinks that increase CO2 concentrations and create further warming. Previous work using paleoclimatic reconstructions has not disentangled the causal effect of interest from the effects of reverse causality and autocorrelation. The response of CO2 to variations in orbital forcing over the past 800,000 years suggests that millennial-scale climate-carbon feedbacks are significantly positive and significantly greater than century-scale feedbacks. Feedbacks are also significantly greater on 100 year timescales than on 50 year timescales over the past 1,500 years. Posterior probability distributions implied by coupled models' predictions and by these paleoclimatic results give a mean of 0.03 for the non-dimensional climate-carbon feedback factor and a 90% chance of its being between -0.04 and 0.09. The 70% chance that climate-carbon feedbacks are positive implies that temperature change projections tend to underestimate an emission path's consequences if they do not allow the carbon cycle to respond to changing temperatures.
Lemoine, D.M., R.J. Plevin, A.S. Cohn, A.D. Jones, A.R. Brandt, S.E. Vergara, and D.M. Kammen. 2010. Environmental Science & Technology 44(19):7347-7350. doi:10.1021/es100418p
Biomass can help reduce greenhouse gas (GHG) emissions by displacing petroleum in the transportation sector, by displacing fossil-based electricity, and by sequestering atmospheric carbon. Which use mitigates the most emissions depends on market and regulatory contexts outside the scope of attributional life cycle assessments. We show that bioelectricity's advantage over liquid biofuels depends on the GHG intensity of the electricity displaced. Bioelectricity that displaces coal-fired electricity could reduce GHG emissions, but bioelectricity that displaces wind electricity could increase GHG emissions. The electricity displaced depends upon existing infrastructure and policies affecting the electric grid. These findings demonstrate how model assumptions about whether the vehicle fleet and bioenergy use are fixed or free parameters constrain the policy questions an analysis can inform. Our bioenergy life cycle assessment can inform questions about a bioenergy mandate's optimal allocation between liquid fuels and electricity generation, but questions about the optimal level of bioenergy use require analyses with different assumptions about fixed and free parameters.
Lemoine, D.M. 2010. The Energy Journal 31(2):113-143.
Plug-in hybrid electric vehicles (PHEVs) enable their drivers to choose whether to use electricity or gasoline, but this fuel flexibility benefit requires the purchase of additional battery capacity relative to most other vehicles. We value the fuel flexibility of PHEVs by representing the purchase of the battery as the purchase of a strip of call options on the price of transportation. We use a Kalman filter to obtain maximum likelihood estimates for three gasoline price models applied to a U.S. municipal market. We find that using a real options approach instead of a discounted cash flow analysis does not raise the retail price at which the battery pays for itself by more than $50/kWh (or by more than 15%). A discounted cash flow approach often provides a good approximation for PHEV value in our application, but real options approaches to valuing PHEVs' battery capacity or role in climate policy may be crucial for other analyses.This article copyrighted and reprinted by permission from the International Association for Energy Economics. The article first appeared in The Energy Journal (Vol. 31, No. 2). Visit The Energy Journal online at http://www.iaee.org/en/publications/journal.aspx
Lemoine, D.M., D.M. Kammen, and A.E. Farrell. 2008. Environmental Research Letters 3(1):014003. doi:10.1088/1748-9326/3/1/014003
Plug-in hybrid electric vehicles (PHEVs) can use both grid-supplied electricity and liquid fuels. We show that under recent conditions, millions of PHEVs could have charged economically in California during both peak and off-peak hours even with modest gasoline prices and real-time electricity pricing. Special electricity rate tariffs already in place for electric vehicles could successfully render on-peak charging uneconomical and off-peak charging very attractive. However, unless battery prices fall by at least a factor of two, or gasoline prices double, the present value of fuel savings is smaller than the marginal vehicle costs, likely slowing PHEV market penetration in California. We also find that assumptions about how PHEVs are charged strongly influence the number of PHEVs that can be charged before the electric power system must be expanded. If most PHEVs are charged after the workday, and thus after the time of peak electricity demand, our forecasts suggest that several million PHEVs could be deployed in California without requiring new generation capacity, and we also find that the state's PHEV fleet is unlikely to reach into the millions within the current electricity sector planning cycle. To ensure desirable outcomes, appropriate technologies and incentives for PHEV charging will be needed if PHEV adoption becomes mainstream.
Contributor to A Low-Carbon Fuel Standard for California. Part 1: Technical Analysis (2007)
Commentary on EVs/PHEVs with Dan Kammen in Accenture's Betting on science: Disruptive technologies in transport fuels (2009)
Other Peer-Reviewed Publications
Lemoine, D.M., S. Fuss, J. Szolgayova, M. Obersteiner, and D.M. Kammen. 2012. Climatic Change 113(2):141-162. doi:10.1007/s10584-011-0269-4
Sager, J., J.S. Apte, D.M. Lemoine, and D.M. Kammen. 2011. Environmental Research Letters 6(2):024018. doi:10.1088/1748-9326/6/2/024018
Lemoine, D.M. and D.M. Kammen. 2009. Environmental Research Letters 4(3):039701. doi:10.1088/1748-9326/4/3/039701
Kammen, D.M., S.M. Arons, D.M. Lemoine, and H. Hummel. 2009. In Plug-in Electric Vehicles: What role for Washington?, ed. D.B. Sandalow, 170-191. Washington, D.C.: Brookings Institution Press.
Lemoine, D., J.P. Evans, and C.K. Smith. 2006. Journal of Forestry 104(3):25-31.