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The nexus between the exchange rates and interest rates: evidence from BRIICS economies during the COVID-19 pandemic

Author

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  • Bhavesh Garg
  • K.P. Prabheesh

Abstract

Purpose - This paper aims to investigate whether the interest rate differentials Granger cause expected change in the exchange rate during the COVID-19 period. The study examines if the investors in the international assets and exchange rate markets take advantages of the relevant information obtained during the COVID-19 pandemic. Design/methodology/approach - This paper used daily data ranging from January 31, 2020 to June 30, 2020 and considered BRIICS economies. The study implemented the Toda–Yamamoto’s Granger causality approach to identify the causality between interest rate differentials and exchange rates. For robustness checks, the study used ARLD short-run dynamics to infer causal relations. Findings - Overall, the results indicate that the interest rate differentials improve the predictability of subsequent exchange rate changes in all six BRIICS economies during the COVID-19 period wherein investors are forward-looking. The empirical results pass the robustness checks. Originality/value - There is a lack of studies exploring the relationship between interest rate differentials and exchange rates in the presence of an unanticipated event such as the current pandemic. To the best of the authors’ knowledge, this is the first study to explore the causal linkages between interest rate differentials and expected change in exchange rates, focusing on the COVID-19 outbreak period.

Suggested Citation

  • Bhavesh Garg & K.P. Prabheesh, 2021. "The nexus between the exchange rates and interest rates: evidence from BRIICS economies during the COVID-19 pandemic," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 38(2), pages 469-486, February.
    • Handle: RePEc:eme:sefpps:sef-09-2020-0387
    DOI: 10.1108/SEF-09-2020-0387
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    Citations

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    Cited by:

    1. Naveed, Hafiz Muhammad & HongXing, Yao & Memon, Bilal Ahmed & Ali, Shoaib & Alhussam, Mohammed Ismail & Sohu, Jan Muhammad, 2023. "Artificial neural network (ANN)-based estimation of the influence of COVID-19 pandemic on dynamic and emerging financial markets," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    2. Sushil Kumar Rai & Akhilesh Kumar Sharma, 2023. "Forecasting Exchange Rate Volatility In India Under Univariate And Multivariate Analysis," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 26(1), pages 175-190, March.
    3. Chowdhury, Kushal Banik & Garg, Bhavesh, 2022. "Has COVID-19 intensified the oil price–exchange rate nexus?," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 280-298.
    4. Hong, Zhiwu & Wang, Zhenhan & Li, Xinda, 2024. "Foreign trade and China’s yield curve during the COVID-19 pandemic: An analysis based on an extended arbitrage-free Nelson–Siegel model," Research in International Business and Finance, Elsevier, vol. 70(PB).
    5. Shah, Sayar Ahmad & Garg, Bhavesh, 2023. "Testing policy effectiveness during COVID-19: An NK-DSGE analysis," Journal of Asian Economics, Elsevier, vol. 84(C).

    More about this item

    Keywords

    Uncovered interest rate parity; Granger causality test; Exchange rates; Pandemic; COVID-19; F31; F41; E43; C32;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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