Abstract

Capital flows to emerging market economies can be characterized by periods of abruptly large inflows alternating with periods of abruptly large outflows. Exceptionally high levels of flows have often been associated with financial crises, and identifying such episodes is crucial for understanding the onset of crises. The existing literature, however, relies on ad hoc threshold criteria for identifying such “extreme” episodes. This paper identifies “extreme” episodes from the data using a formal statistical classification. In particular, I employ a three-state Markov regime switching model to characterize extreme episodes of quarterly net capital flows for each country in a sample of 36 emerging market economies from 1980 to 2014. The model identifies 8 percent of the total sample as periods of extreme inflows (“surges”) and 3 percent of the total sample as extreme outflows (“flights”). Compared to the literature, the model identifies fewer episodes as extreme, and the number of episodes varies substantially across countries.

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