Empirically, between 1970 and 2011 the global variables have played the largest role, explaining about 58 percent of the changes in the risk of banking crisis at the country level. Domestic factors— particularly credit growth over the previous five years, short-term debt, and the level of international reserves—are also important contributors to risk. Changes in domestic variables explain 29 percent of all the variation in risk over the sample period.

## **Box 7  Monetary policy, domestic credit growth and country-specific vulnerabilities**

The “imported” easing of monetary conditions through large capital inflows in recent years has contributed to rapid credit expansion, widening current account deficits, and increasing banking sector vulnerabilities in some cases.

The surge of capital flows in the post-crisis period has contributed to lenient domestic credit conditions, directly through cross-border intermediation channels and indirectly through exchange rate and monetary policy spillovers. Regarding the latter, a simple Taylor Rule predicting the monetary policy stance of central banks in developing countries on the basis of domestic conditions (deviation of consumer price inflation from the policy target and the level of slack in the economy) suggests that policy rates were kept lower than normally suggested during periods of large capital inflows (Figure 7. 1 and He & McCauley (2013)).

In this context, domestic credit has grown very rapidly in several developing countries in recent years, increasing the vulnerability of some economies to a rapid tightening of financing conditions. Outstanding credit exceeds 100 percent of GDP in 15 developing economies, and rose as a share of GDP by 15 or more percentage points in about 40 developing economies between 2007 and 2012. The sharpest upsurges were recorded in Thailand, Armenia, China, Malaysia, Morocco and Turkey (Figure 7. 2). Robust real credit growth continued during 2012 and 2013 in Cambodia, Argentina, Armenia, Indonesia, and Paraguay. Monetary, fiscal, and regulatory tightening in several countries, including China, Brazil, India, and Indonesia, has helped contain a further buildup of credit risks, but banks’ exposure to rising interest rates has become an increasing source of concern since the start of QE tapering expectations.

That said, it should be recognized that domestic variables are not entirely independent of external variables. In particular, as discussed in box 7, loose financial market conditions at the global level can feed through to rapid credit growth, exchange rate changes, and fluctuations in reserves at the domestic level.

The main difference between countries is that, while developing economies do not have the policy levers with which to affect global financial conditions, they can influence the extent and manner in which these bleed through into the domestic economy (see following discussion on policy).

# _Model prediction_

Probability models like the one used here to estimate the sensitivity of banking crises to external, domestic, and contagion factors tend to have low predictive power because the events they model are low-probability events.

One measure of the adequacy of predictive power of the model is the proportion of threshold events it correctly predicts (and the proportion of non-events that it correctly predicts). By these measures, the model outlined in column 5 of annex table A4.3 does a reasonable job in predicting banking crises in developing countries—a conclusion supported by the AUROC statistic of more than 80 percent in the preferred model specification (see annex 4 for a discussion of alternative measures of predictive accuracy of the model).

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