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The Dollar Exchange Rate as a Global Risk Factor: Evidence from Investment

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Abstract

Exchange rate fluctuations could influence economic activity not only via the standard trade channel, but also through a financial channel, which operates through the impact of exchange rate fluctuations on borrowers’ balance sheets and lenders’ risk-taking capacity. This paper explores the “triangular” relationship between (1) the strength of the US dollar, (2) cross-border bank flows and (3) real investment. We conduct two sets of empirical exercises—a macro (country-level) study and a micro (firm-level) study. We find that a stronger dollar is associated with lower growth in dollar-denominated cross-border bank flows and lower real investment in emerging market economies. An important policy implication of our findings is that a stronger US dollar has real macroeconomic effects that go in the opposite direction to the standard trade channel.

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Fig. 1

Source: IMF International Financial Statistics and World Economic Outlook; national data; BIS locational banking statistics; Capital IQ; Bloomberg; authors’ calculations

Fig. 2

Source: IMF International Financial Statistics and World Economic Outlook; national data; BIS locational banking statistics; authors’ calculations

Fig. 3

Source: IMF International Financial Statistics and World Economic Outlook; national data; BIS locational banking statistics; Capital IQ; Bloomberg; authors’ calculations

Fig. 4

Source: IMF International Financial Statistics and World Economic Outlook; national data; BIS locational banking statistics; Capital IQ; Bloomberg; authors’ calculations

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Notes

  1. On the theoretical side, several models with financial frictions predict that exchange rate fluctuations have a balance-sheet effect and generate results according to which depreciation is contractionary if firms have foreign currency-denominated liabilities on their balance sheets (for example, Krugman 1999; Céspedes et al. 2004).

  2. All endogenous variables enter in first differences or growth rates, except for the VIX, which enters in log-levels.

  3. “Appendix A” provides a list of all country groups used in our macro- and micro-level empirical analyses. Panel A of Table 4 contains descriptive statistics of all variables used in our benchmark analysis.

  4. As we demonstrate later in this section, our main results are robust to alternative variables orderings (and, in particular, to moving the exchange rate variable in second position). What is more, most of our key results actually strengthen under those alternative variable orderings.

  5. Panel B of Table 4 contains a summary for the variables used in the micro-level analysis.

  6. Non-tradable sectors include all the industries except the following two-digit SIC codes: 1–14 (agriculture, oil and mining), 20–39 (manufacturing). The classification of the countries’ exchange rate regimes is from the IMF Annual Report on Exchange Arrangements and Exchange Restrictions.

  7. In addition to the specifications presented in this section, we also estimate a number of alternative firm-level specifications in order to test the robustness of our results. More concretely, we demonstrate that our key results are robust to reversing the orthogonalisation procedure for the broad US dollar index and the bilateral exchange rate as well as to controlling for a number of additional country-level variables (GDP per capita, inflation, market capitalization, gross national savings, the share of bank debt) and global variables (US interest rates and the VIX), and. All of those additional results are available upon request.

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Acknowledgements

We thank Signe Krogstrup, Amal Mattoo, Linda Tesar, three anonymous referees, participants at the IMF 18th Jacques Polak Annual Research Conference and seminar participants at the Federal Reserve Board for valuable comments and suggestions. Bat-el Berger and Zuzana Filková provided excellent research assistance. The views expressed are those of the authors and not necessarily those of the Bank for International Settlements.

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Authors and Affiliations

  1. Bank for International Settlements, Basel, Switzerland

    Stefan Avdjiev, Catherine Koch & Hyun Song Shin

  2. American University, Washington, DC, USA

    Valentina Bruno

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  1. Stefan Avdjiev
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  2. Valentina Bruno
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Correspondence to Stefan Avdjiev.

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Appendices

Appendix A: Country Groups

1.1 Set of EMEs Used in the Macro (Country-Level) Study

Argentina, Azerbaijan, Brazil, Bulgaria, Chile, Chinese Taipei, Colombia, Costa Rica, Croatia, Czech Republic, Ecuador, Georgia, Hungary, India, Indonesia, Iran, Israel, Korea, Kazakhstan, Malaysia, Mexico, Nigeria, Peru, Philippines, Poland, Romania, Russia, Saudi Arabia, Serbia, Sri Lanka, South Africa, Thailand, Turkey, and Ukraine.

1.2 Set of EMEs Used in the Micro (Firm-Level) Study

Argentina, Azerbaijan, Bulgaria, Brazil, Chile, China, Colombia, Costa Rica, Croatia, Czech Republic, Georgia, Hungary, India, Indonesia, Israel, Korea, Kazakhstan, Malaysia, Mexico, Peru, Philippines, Poland, Romania, Russia, Serbia, South Africa, Thailand, Turkey, Ukraine, Uruguay, Venezuela, and Vietnam.

1.3 Set of EMEs Used in the Micro (Firm-Level) Study with Floating Exchange Rate Regimes

Argentina, Brazil, Chile, Colombia, Czech Republic, Georgia, Hungary, India, Indonesia, Israel, Korea, Malaysia, Mexico, Peru, Philippines, Poland, Romania, Russia, Serbia, South Africa, Thailand, Turkey, Ukraine, and Uruguay.

Appendix B: Data Summary

See Table 4.

Table 4 Descriptive statistics.
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Avdjiev, S., Bruno, V., Koch, C. et al. The Dollar Exchange Rate as a Global Risk Factor: Evidence from Investment. IMF Econ Rev 67, 151–173 (2019). https://doi.org/10.1057/s41308-019-00074-4

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