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Gross inflows and the incidence of credit booms

How can we predict bad credit booms? This column argues that surges in gross private inflows are good predictors of booms in credit markets, especially those booms that end up in a systemic banking crisis. Using quarterly data on gross capital inflows and real credit, gross private inflows remain a useful measure even when accounting for the past history of credit and asset prices The evidence suggests that surges in capital flows may well mean future financial turmoil.

Foreign flows into emerging market economies have surged in the post-crisis period. The surge in gross inflows has come alongside a rapid creation of credit, an excessive increase in stock and housing prices and continued pressure towards further appreciation of the currency in emerging market economies. These developments have reignited the debate on capital inflow management. Empirical research has robustly found that recent and previous financial crisis in both advanced and emerging market economies were preceded by rapid growth in domestic credit and the real appreciation of the currency (Schularick and Taylor 2012, Gourinchas and Obstfeld 2012). On the other hand, others find that massive inflows of capital engender booms in credit and asset markets (Reinhart and Reinhart 2009, Furceri et al. 2011).

Surges in gross inflows and credit booms

In a recent paper (Calderón and Kubota 2012b), we synthesise both strands of the literature to examine whether surges in gross private capital inflows lead to a higher incidence of credit booms, and especially those boom episodes that end up in systemic crises.

Unlike other related research, we assess the linkages between credit markets and capital inflows using:

  • Data on gross inflows rather than net inflows.
  • A comprehensive quarterly data for 71 countries from 1975Q1 and 2010Q4 (instead of annual frequency data).

The dynamics of capital flows and credit markets along the business cycles are better captured using quarterly data (cf. Rothenberg and Warnock 2011, Forbes and Warnock 2011, Calderón and Kubota 2012a). Consequently, fluctuations in gross inflows can be measured more precisely and the assessment of the impact on credit booms of (the overall amount and the different types of) financing flows coming from abroad is better calibrated. Furthermore, the dynamics of net capital inflows will not allow us to capture the ‘two-way capital flows’ phenomena and will not enable us to differentiate appropriately the behavior of foreign investors from that of domestic ones (Forbes and Warnock 2011), thus providing a misleading inference on the amount of capital supplied from abroad.

Identification of credit booms

Identifying credit booms is not a trivial issue. The literature provides us with two competing methodologies. The first one, outlined in Mendoza and Terrones (2008), focuses on excessive growth in real credit per capita (beyond regular cyclical fluctuations) while the second methodology, implemented by Gourinchas, Valdés and Landarretche (2001) – and also applied in Barajas, Dell’Ariccia, and Levchenko (2009) – focuses on disproportionate movements in the ratio of credit to GDP.

Distinguishing between credit booms and bad credit booms

In addition to identifying credit booms, we distinguish bad credit booms from those booms that lead to a soft landing. Credit booms are not always followed by a systemic banking crisis (Tornell and Westermann 2002, Barajas et al. 2009, Calderón and Servén 2011). For instance, Calderón and Servén (2011) find that only 4.6% of lending booms may end up in a full-blown banking crisis for advanced countries whereas its probability is 8.3% and 4.6% for Latin America and the Caribbean and non-Latin American and Caribbean emerging markets. Hence, we define credit booms followed by a systemic banking crisis as ‘bad’ credit booms (cf. Barajas et al. 2009).

Gross inflows precede lending booms

Figure 1 depicts the dynamic trajectory of gross inflows around credit boom episodes. The undertaken event analysis shows that a build-up of capital flows tends to precede booms in credit markets. Gross inflows later slowdown and hit their trough in the fifth-sixth quarter after the start of the lending boom.

Figure 2, on the other hand, shows that not all types of gross inflow behave alike around episodes of credit booms. The build-up in gross inflows that precede lending booms is mainly explained by surges in other investment (OI) and portfolio investment (PI) inflows, with the latter being more volatile than the former around credit boom episodes. In contrast, FDI inflows are relatively insensitive to the developments in credit markets.

Figure 1. Dynamic behavior of overall gross inflows around credit booms

Note: Period T denotes the start of the credit boom as identified by the criterion implemented in Mendoza and Terrones (2008).

Figure 2. Dynamic behavior of gross inflows by type around credit booms

Note: Period T denotes the start of the credit boom as identified by the criterion implemented in Mendoza and Terrones (2008).

Our results

Our Probit analysis confirms that gross private inflows contain information to predict subsequent booms in credit markets. This result is robust to changes in the sample of countries, the criteria to define credit booms and changes in the set of explanatory variables. So far, the literature has shown that increasing leverage in the financial system and overvalued currencies are the best predictors of financial crisis (Schularick and Taylor 2012, Gourinchas and Obstfeld 2012). Our findings suggest that, even after controlling for these variables, surges of capital inflows are a good indicator of future financial turmoil.

As illustrated by Figure 2, our econometric analysis also confirms that not all types of flows have the same effect on the probability of lending booms. Credit booms are more likely to take place if the surges in capital inflows are driven by gross other investment inflows and, to a lesser extent, by increases in gross portfolio investment (FPI) inflows. Surges of gross foreign direct investment (FDI) inflows would, at best, reduce the likelihood of credit booms. Interestingly, the main conduit is gross other investment bank inflows when we unbundle the effect of gross private other investment inflows on credit booms.

How important is the contribution of gross inflows to the probability of credit booms? Marginal effects from our Probit estimates suggest that the probability of having a credit boom is almost 0.3 greater when there are surges in gross other investment inflows. If these surges are driven by gross other investment bank inflows, this probability is 0.4 greater.

Gross inflows also help predict bad credit booms

Surges in gross inflows not only precede credit booms but also those that coincide or are followed by systemic banking crises. In fact, the likelihood of bad credit booms is greater when surges in capital inflows are driven by increases in other investment inflows. However, the evidence on the impact of gross foreign direct investment and foreign portfolio investment inflows is somewhat mixed. In sum our findings suggest that surges in capital flows are also a good indicator of future financial turmoil. This result holds even when controlling for the increasing leverage in the financial system and overvalued currencies.


Barajas, A, G Dell’Ariccia, and A Levchenko (2009), “Credit Booms: the Good, the Bad, and the Ugly”, Washington, DC: IMF, manuscript.

Calderón, C, and M Kubota (2012a), “Sudden stops: Are global and local investors alike?”, Journal of International Economics, forthcoming.

Calderón, C, and M Kubota (2012b), “Gross Inflows Gone Wild: Gross Capital inflows, Credit Booms and Crises”, The World Bank Policy Research, 6270, November.

Calderón, C, and L Servén (2011) ,“Macro-Prudential Policies over the Cycle in Latin America”, Washington, DC: The World Bank, manuscript.

Forbes, K J, and F E Warnock (2011), “Capital Flow Waves: Surges, Stops, Flight, and Retrenchment”, NBER Working Paper, 17351, August.

Furceri, D, S Guichard and E Rusticelli (2011), “The Effect of Episodes of Large Capital Inflows on Domestic Credit”, OECD Economics Department Working Papers, 864, May.

Gourinchas, P O, and M Obstfeld (2012), “Stories of the Twentieth Century for the Twenty-First”, American Economic Journal: Macroeconomics, 4(1), 226-265

Gourinchas, P O, R Valdes, and O Landerretche (2001), “Lending Booms: Latin America and the World”, Economia, Spring Issue, 47-99.

Mendoza, E G, and M E Terrones (2008), “An anatomy of credit booms: Evidence from macro aggregates and micro data”, NBER Working Paper, 14049, May.

Reinhart, C M, and V Reinhart (2009), “Capital Flow Bonanzas: An Encompassing View of the Past and Present”, In J A Frankel and C Pissarides (eds.), NBER International Seminar on Macroeconomics 2008, Chicago, IL, University of Chicago Press, 9-62.

Rothenberg, A, F Warnock (2011), “Sudden flight and true sudden stops”, Review of International Economics, 19(3), 509-524.

Schularick, M, and A M Taylor (2012), “Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870–2008”, American Economic Review, 102(2), 1029–1061.

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