Our paper contributes to this literature by focusing on the impact on non-performing loans of climate-related natural disasters.

As mentioned above, extreme weather events may decrease a borrower’s likelihood to repay, increasing credit risk. By the same token of argument, natural disasters trigger a decrease in the value of real assets through physical destruction and loss of functionality (e.g., negative spillovers from destruction of infrastructure), decreasing the value of collateral in secured borrowing. Nonetheless, the overall increase in non-performing loans might be diluted by increases in lending.

An extreme weather event is usually followed by a sharp rise in new loan requests and a contemporary surge of deposit withdrawals, as affected individuals and firms need to make up for the economic damage and an increase in current expenses (Brei et al., 2019). This rise in the demand for credit may not be matched by an increase in supply, keeping low credit growth and raising the incidence of eventual non-performing loans related to the disaster. On the contrary, banks could mitigate the impact of shocks by cutting lending most where their comparative advantage is least (i.e., where competing banks have similar access to information). For instance, banks increase lending in affected areas while decreasing financing in those unaffected areas where they do not have branches (Cortés & Strahan, 2017) and in non-affected regions (Ivanov et al., 2020). In contrast, various papers suggest that banks decrease the supply of credit post-disaster. For example, BSP (2020) uses regional and bank-level data from the Philippines to show a deterioration of loan growth and loan quality in the country’s banking sector after extreme rainfall events between 2014 and 2018.

This paper contributes to this strand of the literature by providing the first systematic crosscountry study on the effect of climate and environmental related physical risks on banking sector stability. It provides generic estimates of the effect of such natural disasters on an entire set of financial sector soundness indicators based on the most comprehensive cross-country historical sample. We also discuss the relevance of our results for policy work in this area.

# **3 Data**

This study uses a large panel dataset at annual frequency which combines data on natural disasters, financial sector soundness and other variables from a variety of sources for the period 1980-2019 and for 184 economies. Our sample covers a large number of countries in all income groups and from all World Bank regions and for the longest time period for which major financial sector indicators of interest are available. Data on the instances of climate change, natural disasters and environmental events are from EM-DAT2 and data on financial sector soundness (with a focus on the banking sector) are obtained by combining information from the World Bank’s Finstat database and the IMF’s Financial Soundness Indicators. Since EM-DAT has a number of data quality issues, such as incomplete information for disasters happening before 2000 and bias towards disasters reported by countries themselves or by UN agencies, we have also looked at other sources of disaster data, such as DISINVENTAR, but find that it would significantly reduce the number of

> 2EM-DAT: The Emergency Events Database - Université catholique de Louvain (UCL) - CRED, D. Guha-Sapir - www.emdat.be, Brussels, Belgium.

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