Detecting capital flow surges in developing countries

Kaya A. I., ERDEN L., ÖZKAN İ.

INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, vol.27, no.3, pp.3510-3530, 2022 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 3
  • Publication Date: 2022
  • Doi Number: 10.1002/ijfe.2335
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, EconLit, Geobase, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.3510-3530
  • Keywords: capital flow surges, developing countries, fixed effect probit model, GSADF procedure, right&#8208, tailed unit root tests, UNIT-ROOT TEST, EMERGING MARKETS, PANEL-DATA, INFLOWS, MODELS, EXUBERANCE, BUBBLES, WAVES, PUSH
  • Hacettepe University Affiliated: Yes


This study investigates excessive movements in capital flows called surges or bonanzas. Contrary to the previous work that extensively uses ad-hoc measures and discretionary thresholds; we adopt a distinctive methodology to detect capital flow surges based on right-tailed unit root tests. Generalized supremum augmented Dickey-Fuller (GSADF) proposed by Phillips et al. (2015) is successfully applied to identify asset price bubbles. Exploiting the technical and conceptual similarities in the formations of asset price bubbles and capital flow surges, we perform the GSADF procedure using quarterly net capital flows data from 43 developing countries. The advantages of this procedure are twofold: it can distinguish the behaviour of volatility and explosiveness and diagnose multiple surges in a series. We identified 727 individual surges, 130 different surge episodes, and 4 global capital flow waves over the periods of 1995-2017. Compared with the existing measures, the application of this surge-detection technique provides a useful tool as a data-driven method with no need for discretionary thresholds. We also investigate the factors triggering capital flow surges, employing the Fernandez-Val and Weidner (2016) bias-adjusted fixed effects probit model and find that domestic factors play a dominant role on the surge occurrences in developing countries.