Climate Change and Long-Run Discount Rates: Evidence from Real Estate

  • Stefano Giglio, Assistant Professor of Finance, Booth School of Business, University of Chicago
  • Matteo Maggiori, Associate Professor of Economics, Department of Economics, Harvard University
  • Johannes Stroebe, Associate Professor of Finance, Stern School of Business, New York University
  • Andreas Weber, PhD Student in Finance Department, Stern School of Business, New York University
A bush shaped as an increasing column chart with a dreary city skyline in the background.


The optimal investment to mitigate climate change depends on the discount rate used to evaluate the investment’s uncertain future benefits. The appropriate discount rate is a function of the horizon over which these benefits accrue and the riskiness of the investment. In this paper, building on an original version in 2017, Engle and his research team estimate the term structure of discount rates for an important risky asset class, real estate, up to the very long horizons relevant for investments in climate change abatement.

Recently updated, the study demonstrates how discount rates estimated from private markets, such as the housing market, can be informative about appropriate discount rates for investments in climate change abatement. It contends that applying average rates of return that are observed for traded assets to investments in climate change abatement is misleading. It shows that the discount rates for investments in climate change abatement that reduce aggregate risk, as in disaster risk models, are bounded above by their estimated term structure for risky housing. These should be below 2.6% for long-run benefits. This insight challenges the many discount rates suggested in the literature and used by policymakers. Their framework also distinguishes between the various mechanisms the environmental literature has proposed for generating downward-sloping discount rates. This will be of significant interest to investment management professionals across the spectrum.

The authors are independent contributors to the Global Risk Institute and are solely responsible for the content of this article.