Climate policy uncertainty and macroeconomic dynamics: Financial amplification and state-dependent effects

Climate policy uncertainty (CPU) poses growing risks to macroeconomic stability, yet its transmission mechanisms remain understood. While the literature has examined general uncertainty, the state-dependent effects of transition risk through the financial system are underexplored. Using U.S. local projections and a two-sector New Keynesian model, this paper examines how CPU shocks propagate across the business cycle. I find that CPU shocks significantly contract investment and credit during economic expansions, whereas their effects are statistically muted during recessions. These dynamics are driven by a brown collateral channel, where uncertainty about the future value of carbon-intensive assets triggers a financial accelerator mechanism. The findings highlight that transition risk operates as a systemic financial shock, suggesting that macro-prudential frameworks must account for the volatility of brown asset valuations. • Climate policy uncertainty represents a distinct source of macro-financial risk. • CPU shocks are contractionary and propagate through financial channels. • The contractionary effects of CPU are concentrated in economic expansions. • Uncertainty about brown asset values drives the financial transmission mechanism. • Countercyclical implementation of climate policies minimizes macroeconomic costs.

Authors

Institutions

Publication Details

Journal
Economic Modelling
Published
2026-02-10
DOI
https://doi.org/10.1016/j.econmod.2026.107523
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Climate policy uncertainty and macroeconomic dynamics: Financial amplification and state-dependent effects

FACUNDO LUNA MALLEA
Economic Modelling
Market Dynamics and Volatility
article

Climate policy uncertainty and macroeconomic dynamics: Financial amplification and state-dependent effects

FACUNDO LUNA MALLEA
article en

Abstract

Climate policy uncertainty (CPU) poses growing risks to macroeconomic stability, yet its transmission mechanisms remain understood. While the literature has examined general uncertainty, the state-dependent effects of transition risk through the financial system are underexplored. Using U.S. local projections and a two-sector New Keynesian model, this paper examines how CPU shocks propagate across the business cycle. I find that CPU shocks significantly contract investment and credit during economic expansions, whereas their effects are statistically muted during recessions. These dynamics are driven by a brown collateral channel, where uncertainty about the future value of carbon-intensive assets triggers a financial accelerator mechanism. The findings highlight that transition risk operates as a systemic financial shock, suggesting that macro-prudential frameworks must account for the volatility of brown asset valuations. • Climate policy uncertainty represents a distinct source of macro-financial risk. • CPU shocks are contractionary and propagate through financial channels. • The contractionary effects of CPU are concentrated in economic expansions. • Uncertainty about brown asset values drives the financial transmission mechanism. • Countercyclical implementation of climate policies minimizes macroeconomic costs.

Economic ModellingVol. 158
Rutgers, The State University of New Jersey (US), Rutgers Sexual and Reproductive Health and Rights (NL)
Climate action
Openalex Percentile: Top 66%
Market Dynamics and Volatility
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.