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Macroeconomics of the Energy Transition

Paper Session

Monday, Jan. 5, 2026 10:15 AM - 12:15 PM (EST)

Philadelphia Convention Center, 201-C
Hosted By: American Economic Association
  • Chair: Gregory Casey, Williams College

Substitution between Clean and Dirty Energy: Evidence from Dynamic Structural Modeling

Gregory Casey
,
Williams College
John Bistline
,
Electric Power Research Institute
Christian Traeger
,
University of Oslo

Abstract

The effectiveness of climate mitigation policies depends on how rapidly they induce substitution toward clean energy and away from dirty energy, i.e. the elasticity of substitution (EoS) between clean and dirty energy. The EoS is notoriously difficult to estimate. We use the REGEN energy system model to estimate the EoS and study how various policies and technology innovations can affect the EoS. Our main findings are as follows. In our baseline scenario, the elasticity of substitution is 5 in 2030 and 2 in 2050. Improvements in certain types of new technology increase the EoS. In particular, lower-cost energy storage technologies and carbon capture and storage (CCS) make variable renewable energy better substitutes for fossil fuels for electricity production. Holding technology fixed, increases in policy stringency decrease the EoS, because the variability issues become more binding as renewable energy penetration increases. Notably, none of the scenarios align with the assumption of a time-constant elasticity of substitution, which is a near-universal feature of macroeconomic models of climate change.

Relying on Intermittency: Clean Energy, Storage, and Innovation in a Macro Climate Model

Claudia Gentile
,
London School of Economics

Abstract

The transition to clean energy technologies is essential to reduce CO2 emissions. One significant challenge associated with renewable energy sources, such as solar and wind, is their intermittency. I study the intermittency problem by introducing a novel micro-founded energy sector with directed technical change in a macro climate model. I show that the aggregate elasticity of substitution between clean and dirty energy is not constant, and it crucially depends on the development of storage technologies. Without policies, the provision of storage technologies is inefficiently low, impeding the transition towards clean, intermittent technologies. In the optimal allocation, the clean energy transition is accelerated with an initial clean energy share increasing from 22.5% to 63.5% and a reallocation of all R&D resources away from dirty energy towards clean energy and, in particular, energy storage technologies. The introduction of clean energy subsidies under the US Inflation Reduction Act is successful at increasing the short-run clean energy share, but insufficient to solve the intermittency problem.

The Macroeconomics of Net Zero

Neil R. Mehrotra
,
Federal Reserve Bank of Minneapolis

Abstract

This paper examines the macroeconomic cost and implications of transitioning to net zero emissions. The macroeconomic cost of achieving net zero is a combination of lower output due to higher energy prices and higher investment due to more costly technology. Along the transition path, a net zero target operates as both an anticipated negative productivity shock and a negative capital shock. Thus, for monetary policy, net zero is a negative aggregate demand shock that lowers the natural rate of interest. Using projected technology costs and net zero modeling scenarios, decarbonization of US electric power generation is estimated to cost less than 0.2% of steady state consumption.

How Firms Cut Carbon: Evidence from the European Emissions Market

Ivan Rudik
,
Cornell University
Andrew Butters
,
Indiana University
Jackson Dorsey
,
University of Texas at Austin

Abstract

The European Union Emissions Trading System (EU ETS), established in 2005, is the largest carbon pricing scheme in history. In the first 15 years of the program, emissions from regulated stationary sources have fallen by more than 30%. Understanding the mechanisms behind these reductions is critical for assessing the effectiveness of carbon pricing and informing future policy design. This paper examines how EU ETS has shaped market outcomes and firm technological change to understand how EU ETS delivered emissions reductions. We use a panel dataset of over 5,000 firms from 2005-2021 to decompose observed emissions reductions into input substitution, reallocation across firms, and clean technological change. We first estimate a production function where emissions are an input into production. We find that the firm-level micro-elasticity of substitution between emissions and other inputs is near zero, particularly in the energy sector, suggesting abatement through changing input mixes is costly. However, we find that the aggregate elasticity of substitution at the market-level is much higher, indicating how across-firm reallocation of production from dirtier to cleaner firms led to emissions reductions. Finally we estimate that there have been improvements in clean technology by nearly 50% over this timeframe, accounting for most of the emissions reductions, with the energy sector exhibiting some of the fastest technology advances. By combining rich microdata with a structural model of production and demand, our study sheds new light on the mechanisms behind firm-level responses to carbon pricing. These findings offer important insights for policymakers designing carbon policies that balance environmental objectives with industrial competitiveness.

Discussant(s)
Shifrah Aron-Dine
,
Stanford University
Ishan Nath
,
Federal Reserve Bank of San Francisco
Gernot Wagner
,
Columbia University
Jonathan Colmer
,
University of Virginia
JEL Classifications
  • E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy
  • Q4 - Energy