In Search of Global Determinants of National Credit-to-GDP Gaps

Risks. 2022. Vol. 10. No. 12.

Stolbov M., Shchepeleva M.

This paper seeks to identify the most important global drivers of credit-to-GDP gaps for 35 countries. The analysis is performed on a country-by-country basis for the sub-periods 2000Q1:2007Q2, 2007Q3:2013Q4, and 2014Q1:2021Q1 and is based on two state-of-the-art methods for variable selection in the time series framework: the one covariate at a time multiple testing (OCMT) and adaptive least absolute shrinkage and selection operator (LASSO). We find that the number of salient global factors tends to increase over time, reaching its maximum during the post-crisis period. This period is also marked by a pronounced role of the global factors capturing the stance of the US monetary policy, while in the preceding sub-periods, the most significant factors are global credit conditions (the TED spread) and world industrial production, respectively. Regardless of the sub-periods, advanced economies’ credit-to-GDP gaps appear more dependent on the global factors than the gaps in emerging markets. In addition, we identify country-specific variables which shape the susceptibility of the national credit-to-GDP gaps to the global factors.

Keywords: random forest, credit-to-GDP gap, global factors, variable selection