Financial stability

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Credit-to-GDP gaps

Credit-to-GDP gaps

carol.reyes.dulong
Open Dataset
Creators: BIS statistics
Publication Date: 2025-03-11
Creators: BIS statistics

The credit-to-GDP gap data set aims at quantifying the notion of “excessive credit” in a simple way. It serves as an early warning indicator for potential banking crises or severe distress.

The data set covers 44 economies, starting at earliest in 1961 and captures total borrowing from all domestic and foreign sources. The credit-to-GDP gap is defined as the difference between the credit-to-GDP ratio and its long-run trend. The trend is derived using a one-sided (ie backward-looking) Hodrick-Prescott filter.

To facilitate comparability across countries, the credit-to-GDP ratio, as published in the BIS database of total credit to the private non-financial sector, is used as input data. However, it also means that the credit-to-GDP gaps published by the BIS may differ from those used by national authorities as part of their countercyclical capital buffer decisions.

The gap indicator was adopted as a common reference point under Basel III to guide the build-up of countercyclical capital buffers. Authorities are expected, however, to apply judgment in the setting of the buffer in their jurisdiction after using the best information available to gauge the build-up of system-wide risk rather than relying mechanistically on the credit-to-GDP guide. For instance, national authorities may form their policy decisions using credit-to-GDP ratios that are based on data series that differ from the BIS series, leading to credit-to-GDP gaps that differ from those published by the BIS.

Debt service ratios

Debt service ratios

carol.reyes.dulong
Open Dataset
Creators: BIS statistics
Publication Date: 2025-03-11
Creators: BIS statistics

The data set for debt service ratios reflects the share of income used to service debt for households, non-financial corporations and the total private non-financial sector. It provides important information about interactions between the financial and real sectors, and is a reliable early warning indicator for systemic banking crises.

The published series for the total private non-financial sector cover 32 economies, starting at earliest in 1999. The data set also includes a breakdown for households and non-financial corporations, estimated for 17 economies.

To derive the DSRs on an internationally consistent basis, the BIS applies a unified methodological approach and uses, where available, input data compiled on an internationally consistent basis (total stock of debt, income available for debt service payments, average interest rate on the existing stock of debt and the average remaining maturity). Although the applied methodology is subject to an approximation error when aggregate data are used, it correctly captures how the DSR in a particular country changes over time. However, it may not accurately measure the DSR level compared with the result that may be obtained from micro data.

For practical purposes, it is more meaningful to compare national DSRs over time (eg by removing country-specific means) rather than to compare their absolute levels, which are difficult to pinpoint. This approach also takes account of different institutional and behavioural factors affecting average remaining maturities.

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