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IMF Working PaperResearch DepartmentTime-Varying Impacts of Government Spending on CO2 EmissionsPrepared byStefano Di Bucchianico, Mario DiSerio, Matteo Fragetta and Giovanni MelinaAuthorized for distribution byFlorence JaumotteJuly2025IMF Working Papersdescribe research in progress by the author(s) and are published to elicitcomments and to encourage debate.The views expressed in IMF Working Papers are those of theauthor(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.ABSTRACT:A Bayesian factor-augmented interacted vector autoregression framework purified ofexpectations is employed to analyze how government spending shocks have impacted CO2 emissions in theUnited States from the 1980s to the pre-pandemic period. Consumption-generated emissions are found to havegenerally risen following fiscal expansions, although their elasticity to government spending has declinedsubstantially over time—with the five-year elasticity dropping from about 0.5 in the early 1980s to 0.1 by 2019.In contrast, positive government spending shocks increased production-generated emissions in the early1980s—with a five-year elasticity near 0.4—but reversed course by the 1990s, eventually reaching an elasticityof–0.5 by the end of the sample. Examination of time-varying interaction variables suggests that environmentalregulation, tertiarization, and a larger share of spending on public goods can mitigate—or even reverse—theemissions growth associated with economic expansions driven by government spending. Furthermore,government consumption, rather than investment, is chiefly responsible for these shifts in emissions elasticities.RECOMMENDED CITATION:Di Bucchianico S., M. Di Serio, M. Fragetta and G. Melina (2025).“Time-VaryingImpacts of Government Spending on CO2 Emissions,”IMF Working Paper No. 25/132, International MonetaryC32, C38, E62, Q54, Q58government spending; fiscal policy; CO2 emissionsmdiserio@unisa.it; mfragetta@unisa.it; gmelina@imf.orgStefano Di Bucchianico acknowledges funding from the Italian MUR through the PRIN 2022 PNRR project Disentangling theEnvironmental andenergy efficiency impact of public innovation investment for a greentransition (DEMETRA) (P2022SRW8N,CUP D53D23017910001) financed by the European Union.Theauthorsthank Giovanni Angelini, Matteo Ciccarelli, Marwil Dàvila,Andreas Dibiasi, Sergio Destefanis, Giovanni Pellegrino, and Peter Skott forusefulcomments. *Fund, Washington, D.C.JEL Classification Numbers:Author’s E-Mail Address: Keywords: * INTERNATIONAL MONETARY FUNDTime-Varying Impacts ofGovernment Spending on CO2EmissionsPrepared byStefano Di Bucchianico, Mario Di Serio, Matteo Fragetta andGiovanni Melina Contents1Introduction2Methodology2.1Empirical Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2.2Data and Baseline Specification. . . . . . . . . . . . . . . . . . . . . . . . .2.3Inference, Identification, and Computation of Cumulated CO23Results3.1Cumulative CO2 Elasticities to Government Spending . . . . . . . . . . . . .3.2Drivers of CO23.3Cumulated CO2vestment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4ConclusionsADataA.1Endogenous Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A.2Exogenous Variable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A.3Informational Dataset. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .List of Tables1Average Cumulative CO22Average Cumulative CO23Average Cumulative CO2List of Figures1Proxies for Channels Governing the Impact of Fiscal Policy on CO22Cumulative CO23Distributions of Dierences in Cumulative Emission Elasticitied Between thePre- and Post-2000q3 Periods. . . . . . . . . . . . . . . . . . . . . . . . . .4Cumulative Consumption-Generated CO2Partial Correlations with Proxies of Key Determinants. . . . . . . . . . . . 69910Elasticities . .131515Emission Elasticities . . . . . . . . . . . . . . . . . . . . . . .19Emission Elasticities to Government Consumption and In-202530303131Emission Elasticities . . . . . . . . . . . . . . . . .17Emission Elasticities—Government Consumption.24Emission Elasticities—Government Investment. .26Emissions13Emission Elasticities . . . . . . . . . . . . . . . . . . . . . .1618Emission Elasticities: Rolling-Window214 5Cumulative Production-Generated CO2Emission Elasticities: Rolling-WindowPartial Correlations with Proxies of Key Determinants. . . . . . . . . . . .226Cumulative CO2Emission Elasticities—Government Consumption . . . . . .237Cumulative CO2Emission Elasticities—Government Investment. . . . . . .255 1IntroductionWhile a substantial body of research has examined the link between economic activity andCO2emissions (Dinda, 2004; Stern, 2017; Cohen et al., 2018), the specific impact of govern-ment spending on emissions has been understudied. The few studies on the topic often reportconflicting findings (Bernauer and Koubi (2013); Chishti et al., 2021; Halkos and