Capital flow waves: Surges, stops, flight, and retrenchment

Almost all earlier work on extreme international capital-flow episodes was built on proxies for net capital flows, which cannot tell a change in foreign behaviour from a change in domestic behaviour. This paper rebuilds the measurement from gross flows and dates four distinct episode types: “surges” and “stops” (sharp increases and decreases in gross inflows, driven by foreigners) and “flight” and “retrenchment” (sharp increases and decreases in gross outflows, driven by domestic residents). Using quarterly IMF data on gross inflows and outflows for 58 emerging and developed economies from 1980 (at the earliest) through 2009 – a sample that captures $10.8 trillion of gross inflows in 2007, or 97% of global inflows recorded by the IMF, and excludes China for want of quarterly data – it identifies 167 surge, 221 stop, 196 flight and 214 retrenchment episodes, each lasting roughly a year on average. Switching from net to gross flows changes the picture sharply: at the height of the crisis (2008Q4-2009Q1) the net-flow method finds 13 surges and 22 stops where the gross-flow method finds 1 surge and 47 stops, because in country after country a stop of foreign inflows coincided with domestic residents bringing money home, and the net measure read that combination as a “surge”. Estimating the conditional probability of each episode type on lagged global, contagion and domestic variables (a complementary log-log model on 54 countries, 1985-2009, with errors correlated across episode types and clustered by country), the paper finds global risk – proxied by the VXO – is the only variable significantly associated with all four types: positively with stops and retrenchment, negatively with surges and flight. Contagion through trade linkages, banking linkages or simple regional proximity is strongly associated with stops and retrenchment. Domestic characteristics are generally much weaker and often not robust, and there is no significant association between capital controls and the probability of a surge or a stop. The authors are explicit that they do not assess causation, that flight episodes are the most idiosyncratic and hardest to explain, and that the results are correlations between lagged conditioning variables and episode incidence rather than estimated policy effects.

Kristin J. Forbes | Macro Paper Warehouse

Capital flow waves: Surges, stops, flight, and retrenchment