Climate change adaptation efforts are heavily dependent on a country's fiscal capacity and the associated costs of undertaking adaptation policies. The current accumulation of high debt levels in emerging and low-income developing countries, which are disproportionately affected by climate...

In response to the growing threat of climate change, the insurance industry has made significant investments in modelling and quantifying physical climate risks. However, the emerging risk of climate litigation has proven particularly difficult to model. In 2015 Mark Carney, then-Governor of the...

Without reliable seasonal climate forecasts, farmers and managers in other weather-sensitive sectors might adopt practices that are optimal for recent climate conditions. To demonstrate this principle, crop simulation models driven by a dense meteorological network were used to identify...

We investigate carbon risk in global equity prices. We develop a measure of carbon risk using industry standard databases and study return differences between brown and green firms. We observe two opposing effects: Brown firms are associated with higher average returns, while decreases in the...

We offer an applied approach to the double materiality assessment of environmental, social and governance (ESG) matters, which could serve as practical guidance to the 60K companies required by EU regulation (CSRD) to carry out this assessment. Focussing on the financial materiality of climate...

This paper analyses the exposure to climate risk of ABS, an asset class frequently pledged as collateral in the European Central Bank (ECB) refinancing operations. This paper focuses on ABS backed by auto loans or loans granted to Small and Medium Enterprises (SMEs) and explores ways to measure...

This paper identifies individual and regional risk factors for hospitalizations caused by heat within the German population over 65 years of age. Using administrative insurance claims data and a machine-learning-based regression model, we causally estimate heterogeneous heat effects and explore...

This paper uses machine learning to improve the prediction of corporate emissions so that financial regulators and investors can make better decisions about climate transition risk. The need for predictions arises because only a subset of global companies report emissions. The novelty is to use...

Catastrophe insurance markets have changed beyond recognition since the sudden upturn in claims beginning in 1966. There is now a growing tendency for risk manager to bypass traditional insurance markets, and a variety of instruments designed directly to transfer risk to the financial markets....

This paper surveys state-mandated programs designed to provide natural catastrophe insurance to property owners and businesses unable to find a policy in the private market. The paper provides an overview of the 10 state programs offering wind or earthquake coverage and outlines the motivation...