Center for Energy and the Economy working papers

Abstract: We propose a semiparametric local projection estimator of nonlinear impulse response functions for a broad class of structural dynamic models relevant for applied macroeconomics, including models with nonlinearly transformed regressors, state dependent coefficients and nonlinear interactions between shocks and state variables. The estimator is based on a doubly robust moment condition that identifies the average response function as a linear functional of a nonparametric conditional mean, augmented by a density ratio that captures the effect of shifting the shock of interest. We combine this moment condition with cross-fitting that handles serial dependence. The resulting estimator is √  T -consistent and asymptotically normal. We examine the finite-sample performance of the estimator across a range of nonlinear data generating processes and illustrate its use in two empirical examples.

DOI: https://doi.org/10.24149/wp2616

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Abstract: The 2026 Iran war has raised the question of how exposed the U.S. economy is to geopolitical oil supply disruptions. It is widely believed that the U.S. economy has become less vulnerable to such disruptions as it has reduced its dependence on oil and changed from a major net oil importer to a net oil exporter. We develop a two-country model of the global economy with large geopolitical oil supply disruptions that distinguishes between the U.S. economy and the rest of the world. We find that the response of U.S. real GDP growth to the disruption in global oil supplies today is only one-twentieth of what it would have been in 1980. Moreover, the response of U.S. real GDP growth today is only one-sixth of the decline in the rest of the world.

DOI: https://doi.org/10.24149/wp2615

Appendix DOI: https://doi.org/10.24149/wp2615app

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Abstract: Despite the importance of program participation for policy, treatment effects are often measured on self-selected samples. We study electric vehicle (EV) managed charging, intended to reduce electric grid strain by optimally allocating charging across EVs. Prior work finds large impacts of managed charging among households who volunteer for an RCT. In contrast, we test managed charging with an experiment including all EVs within a California utility. Enrollment is low even with high incentives, and we can reject even modest intent-to-treat effects on electricity consumption. Managed charging is less effective than previously thought, underscoring the value of population-wide experiments.

DOI: https://doi.org/10.24149/wp2610

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Abstract: This paper shows how to assess the inflationary impact of the rise in the price of oil caused by the 2026 Iran War. We first generate projections of the quarterly price of oil from a calibrated DSGE model of the global economy under a range of scenarios and then incorporate these projections into a monthly VAR model of the impact of U.S. gasoline price shocks on inflation and inflation expectations. Our analysis speaks to the magnitude and persistence of the impact of higher oil prices on headline and core PCE inflation and on household inflation expectations.

DOI: https://doi.org/10.24149/wp2609

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Abstract: Artificial-intelligence-driven data centers are reversing two decades of flat U.S. electricity demand and have generated questions about how this growth will impact electricity prices. We quantify this effect using an hourly, unit-level least-cost dispatch model covering wholesale electricity markets in the continental United States. We find that existing data centers have already increased wholesale prices by 3 to 5% on average nationwide, with substantially larger effects in regions hosting major data center corridors. Extending the model through 2028, we show that if proposed construction proceeds under high-utilization scenarios, wholesale prices could rise dramatically (50%), while more moderate build-out yields smaller (20%) but still meaningful effects. Impacts vary due to utilization and build-out assumptions. Finally, we use the model to address several policy discussions including optimal data center siting decisions and renewable build-out uncertainty.

DOI: https://doi.org/10.24149/wp2606

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Abstract: This paper proposes mean group and pooled estimators of impulse responses based on mixed-frequency auxiliary distributed lag (DL), autoregressive distributed lag (ARDL) or vector autoregressive distributed lag (VARDL) estimating equations. Our setup assumes that the data are generated by a high-frequency VAR process. While the shock of interest is directly observed at high frequency, the outcome variable is only observed as a temporally aggregated variable at a lower frequency. We derive the asymptotic distributions of the six proposed estimators. Monte Carlo experiments show that pooled estimators generally perform better than the corresponding mean group estimators for relevant sample sizes. An empirical illustration to the pass-through from daily wholesale gasoline price shocks to monthly consumer price inflation illustrates the usefulness of the proposed methods.

DOI: https://doi.org/10.24149/wp2603

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Abstract: Electricity distribution network constraints may ultimately limit the pace of transportation electrification. This paper examines the underappreciated challenges that electric vehicle (EV) adoption poses for the distribution grid. While prior research has focused on bulk power and private service upgrades, we emphasize how local distribution capacity is strained by reduced load diversity at small aggregations. We highlight two alternatives to costly infrastructure expansion: (1) demand-based tariffs that allocate scarce distribution capacity more efficiently, and (2) managed charging programs that coordinate EV loads within local limits. While managed charging reduces transformer overloads and smooths load profiles, consumer participation remains a barrier. Economists can play a key role by designing rate structures that align user incentives with local network constraints and by evaluating consumer acceptance of these solutions as electrification advances.

DOI: https://doi.org/10.24149/wp2540

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Abstract: In open economies, the effectiveness of carbon taxes is diminished by “pollution leakage,” where some polluting activity shifts abroad because of the tax. This paper shows that the same conditions that lead to pollution leakage enhance the efficacy of clean subsidies. As a result, the optimal policy in an open economy combines a pollution tax and a clean subsidy, the balance of which depends on the leakage rate. Furthermore, efficient policy sets the sum of the tax and subsidy rates, a measure of policy ambition, equal to the marginal damages from pollution, and does not depend on the leakage rate.

DOI: https://doi.org/10.24149/wp2533

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Abstract: Pigouvian subsidies are efficient, but output subsidies with uncertain or limited durations are not Pigouvian. We show that optimal “time-limited” policies must also subsidize investment to correct externalities generated after the output subsidy ends. Furthermore, an output subsidy’s optimal duration is characterized by the change in production when it ends. In the wind-energy industry, we find that power generation decreases by 5-10% after the end of facilities’ ten-year eligibility for the Renewable Energy Production Tax Credit. This behavioral response has implications for energy transitions and highlights how time limits could cause larger distortions in more elastic industries.

DOI: https://doi.org/10.24149/wp2530

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Abstract: We estimate the effect of competition on incumbent firm pricing by using high frequency price data and the precise geographic location for all gas stations in California. Using an event study design, we find that the entry of a new station is associated with a 2.7 cent decrease in prices at incumbent stores, which equates to a 7 percent reduction in estimated retail markups. The effects are immediate, persistent. In contrast, nearby exit results in precisely estimated null effects on prices. We show that these results are consistent across all fuel blends, dissipate with distance and are driven by less concentrated markets. Finally, we explore the asymmetric effects, showing that the difference cannot be attributed to differences in branding, proximity to highway or data quality idiosyncrasies, although we find suggestive evidence that exit tends to happen in more competitive markets and among less heavily trafficked stations.

DOI: https://doi.org/10.24149/wp2509r1

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