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Climate Risk and Asset Pricing

Paper Session

Monday, Jan. 5, 2026 8:00 AM - 10:00 AM (EST)

Loews Philadelphia Hotel, Commonwealth Hall B
Hosted By: American Finance Association
  • Riccardo Colacito, University of North Carolina-Chapel Hill

Carbon Burden

Lubos Pastor
,
University of Chicago
Robert Stambaugh
,
University of Pennsylvania
Luke Taylor
,
University of Pennsylvania

Abstract

We quantify the U.S. corporate sector's future carbon damages by computing its ``carbon burden"---the present value of social costs of its future carbon emissions. Our baseline estimate of the carbon burden is 131% of total corporate equity value. Even with indirect emissions excluded, 13% of firms have carbon burdens exceeding their market capitalizations. The 30 largest emitters account for all the decarbonization of U.S. corporations predicted by 2050. Predicted emission reductions, and even firms' targets, fall short of the Paris Agreement. Carbon burden is priced: firms with higher burdens have higher costs of capital, even controlling for past emissions.

A Market-Based Measure of Ambiguity Aversion: Housing Prices Under Rising Seas

Michael Barnett
,
Arizona State University
Jacob Dice
,
Federal Reserve Bank of Kansas City
Toan Phan
,
Federal Reserve Bank of Richmond
David Rodziewicz
,
Federal Reserve Bank of Kansas City
Constantine Yannelis
,
University of Cambridge

Abstract

We examine how ambiguity aversion shapes real estate market responses to long-run sea-level rise (SLR) risk. We link theory and empirics to quantify ambiguity aversion, and explore how this parameter impacts real estate markets and raises homeowners’ willingness to invest in climate change adaptation. Using a novel dataset of projected inundation times for over two million coastal homes, we show that housing prices reflect both expected SLR risk and uncertainty across climate scenarios. We estimate an ambiguity aversion parameter, and find that this shifts probability weights toward worst-case scenarios, substantially increasing the weight on the most extreme SLR projections. Our paper provides the first market-based estimates for ambiguity aversion parameters in the field. We further use our model and estimates to provide new estimates for very long-run discount rates.

Two Centuries of U.S. Innovation: Firms' Internal Networks and Resilience to Disasters

Mathias Kruttli
,
Indiana University
Noah Stoffman
,
Indiana University
Sumudu Watugala
,
Indiana University

Abstract

Using advanced machine learning methods, we construct a comprehensive database of the universe of approximately 12 million U.S. patents from 1836 to 2023. We analyze the resilience of innovation to disaster shocks using hurricane landfall data spanning two centuries. Major hurricanes destroy local innovative capacity for up to a decade and lead to permanent losses relative to the counterfactual. Multi-location firms reallocate resources from establishments in the landfall region and increase innovation in establishments elsewhere in the aftermath of a hurricane. These positive spillovers along firms' internal networks increase aggregate innovation in counties distant from the hurricane.

Allocative Efficiency of Green Finance Instruments

Kai Li
,
Peking University
Yicheng Wang
,
Peking University
Chenjie Xu
,
Shanghai University of Finance and Economics

Abstract

This paper investigates the allocative efficiency of green finance instruments through a general equilibrium model with heterogeneous firms and financial frictions. We emphasize the impact of the timing of financial instruments—'ex-post', such as carbon taxes, versus 'ex-ante', like green credit schemes—on the distribution of dirty capital and its environmental implications. Our study reveals that ex-post instruments inadvertently direct dirty capital towards financially constrained firms with higher emission intensity, potentially exacerbating economy-wide emission. Conversely, ex-ante instruments yield beneficial redistributions. The study emphasizes the significance of incorporating the distributive effects of green finance tools into their design and advocates for a general equilibrium viewpoint to evaluate their effectiveness comprehensively, highlighting the pivotal role of instrument timing.

Discussant(s)
Tuomas Tomunen
,
Massachusetts Institute of Technology
Jarda Borovicka
,
New York University
Pedro Matos
,
University of Virginia
Lorenzo Garlappi
,
University of British Columbia
JEL Classifications
  • G0 - General