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International Capital Flows and Extreme Exchange Market Pressure: Evidence from Emerging Market Economies

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Abstract

In response to the currency crises in the emerging market economies (EMEs) during the 1990s, earlier studies tended to put emphasis on identifying and explaining currency crash, which is an extreme event mostly associated with massive capital reversals. After the 2008 global financial crisis, the focus shifted towards enormous capital inflows which have put a sharp appreciation pressure on domestic currency and inflated a large housing and construction bubble. In this paper, we examine the foreign exchange instabilities of a group of EMEs between 1995Q1 and 2019Q4 using the exchange market pressure (EMP) index by taking into considerations both extreme positive and negative episodes. The identification of tail observations is carried out under the framework of Extreme Value Theory (EVT) to handle asymmetric and heavy-tailed data. A panel multinomial logit model is used to explore whether the predictors differ between extreme positive and negative EMP events. Our findings show that (1) there is asymmetry in the EMP distributions, where the occurrence of currency crises is more frequent than excessive appreciations in most EMEs, (2) portfolio and credit flows are significant predictors to both extreme events, and (3) by distinguishing the residency of capital flows, foreign credit flow is the key factor that contributes to the devaluation pressure in the EMEs.

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Notes

  1. One such example is Endaka Fukyo, which is a recession period faced by Japan as net exports deteriorated due to strong yen revaluation in the aftermath of 1985 Plaza Accord agreement (Obstfeld 2009)

  2. For instances, Weymark (1995, 1998), Burdekin and Burkett (1990) conduct EMP research for Canada; Connolly and Da Silveira (1979) for Brazil; Brissimis and Leventakis (1984) for Greece; Kim (1985) for Korea; Thornton (1995) for Costa Rica; Baig et al. (2003) for India; Parlaktuna (2005) for Turkey; Jeisman (2005) for Australia; De Macedo et al. (2009) for five African countries.

  3. Pentecost et al. (2001) propose Principal Component Analysis (PCA) to determine weights of EMP components. Hegerty (2013) compare PCA measure with variance-weighted measures. He finds that many countries’ EMP components do not produce appropriate principal components and concludes that PCA measure might not serve as a definitive improvement over the variance-weighted measure.

  4. For instance, Komulainen and Lukkarila (2003) define threshold as mean plus 2 standard deviations. Kaminsky and Reinhart (2000) use threshold of mean plus 3 standard deviations.

  5. According to Mundell-Fleming model, at a given policy rate, capital inflows are contractionary to the real economy through exchange rate appreciation (Blanchard et al. 2016). Kappler et al. (2013) identify large nominal and real appreciations and find that these episodes are associated with deterioration in current account balances. Mehrotra (2007) finds that in both Japan and Hong Kong, an appreciation in nominal effective exchange rate leads to a statistically significant decline in real output and price level. Ghosh and Rajan (2007) study the degree of nominal effective exchange rate pass-through into the export prices of Korea, Thailand and Singapore and find asymmetric pass-through between appreciation and depreciation.

  6. Other investments consist mostly of foreign bank lending, which are also known as credit inflows in other studies (Rey 2015)

  7. Using 4-quarter moving sum of capital inflows data, we compute the rolling means and standard deviations of the year-over-year(yoy) changes of capital inflows over 12 quarters. Extreme capital inflows episodes are determined when three criteria are met: (1) current yoy changes exceed two-standard-deviations band, (2) the episode lasts for all consecutive quarters for which the yoy changes exceed one-standard-deviation band, (3) the length of the episode is greater than one quarter.

  8. df is allowed to take an increment of 0.1 from 1 to 5 and 0.2 from 5 to 10.

  9. k is allowed to vary from 1% to 20% of n.

  10. As US interest rate is used to compute EMPit, it enters as lag into RHS of Eq. 1 to avoid endogeneity problem.

  11. In light of possible fixed effect, the hybrid multinomial logit approach as proposed by Allison (2009) is adopted for further sensitivity check. The qualitative findings are largely similar to our baseline results which are available upon request.

  12. We also control for a third group in which both extreme positive and negative episodes occur within the same quarter. The result is not reported as there are only 36 observations fall within this group.

  13. Correlation between reserve to GDP ratio and Chinn-Ito financial openness index is 0.14 at 1% significance level.

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Acknowledgments

We gratefully acknowledge the funding support from Singapore Ministry of Education AcRF Tier 1 Research Grant (RG77/18). We would also like to thank the editor and two anonymous referees for their insightful comments and suggestions.

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  1. Department of Economics, Nanyang Technological University, School of Social Sciences, 14 Nanyang Drive, Singapore, 637332, Singapore

    Sook-Rei Tan, Wei-Siang Wang & Wai-Mun Chia

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  1. Sook-Rei Tan
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Appendix

Appendix

Table 10 List of emerging market economies
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Table 11 Description of variables
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Tan, SR., Wang, WS. & Chia, WM. International Capital Flows and Extreme Exchange Market Pressure: Evidence from Emerging Market Economies. Open Econ Rev 32, 479–506 (2021). https://doi.org/10.1007/s11079-020-09599-y

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