With average temperature ranging from− 20° C at the North Pole to 30° C at the Equator and
with global warming expected to reach 1.4° C to 4.5° C by the year 2100, it is clear that …

Traditional climate strategies focus on long-term emissions targets, neglecting cumulative
CO 2 emissions and often limiting their scope to territorial emissions. Additionally, individual …

We introduce deep equilibrium nets (DEQNs)—a deep learning‐based method to compute
approximate functional rational expectations equilibria of economic models featuring a …

Climate change will impact current and future generations in different regions very
differently. This paper develops the first large-scale, annually calibrated, multi-region …

Emissions pathways used in climate policy analysis are often derived from integrated
assessment models. However, such emissions pathways do not typically include climate …

This paper proposes a global algorithm to solve a large class of nonlinear continuous-time
models in finance and economics. Using tools from machine learning, I recast problem of …

We develop an algorithm for solving a large class of nonlinear high-dimensional continuous-
time models in finance. We approximate value and policy functions using deep learning and …

This paper analyzes how climate risks are priced on financial markets. We show that climate
tipping thresholds, disagreement about climate risks, and preferences that price in long-run …

Investors and regulators are increasingly concerned that climate changes, tipping points in
particular, pose serious risks for future economic growth. The authors extend a leading …

This paper provides scientific starting points for climate-economy modeling. The sensitivity of
climate change to emissions of greenhouse gases is uncertain. The same is true about the …