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Exchange rate movements in emerging economies - Global vs regional factors in Asia

Author

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  • Raphael Chiappini

    (Larefi - Laboratoire d'analyse et de recherche en économie et finance internationales - UB - Université de Bordeaux)

  • Delphine Lahet

    (Larefi - Laboratoire d'analyse et de recherche en économie et finance internationales - UB - Université de Bordeaux)

Abstract

The aim of this article is to analyse the main determinants of emerging markets' exchange rate movements, particularly in Asia. For this purpose, we implement a dynamic latent factor model to investigate the drivers of 24 emerging countries' exchange rate movements and decompose the patterns into three components: a global common factor, a regional factor and a country-specific factor. Our results reveal that, in the whole period of 2000–2015, the common global factor is by far the most important determinant of exchange rate variations for Asian economies and, albeit to a lesser extent, for Latin America. However, after 2005, there is a strong increase in the explanatory power of the regional factor in Asia, from 5.6% to 45.1%, and to 49.7% in the period of 2011–2015, which shows that it is becoming the dominant factor in this area. Then, we use a Vector Autoregressive (VAR) model and an Autoregressive Distributed Lag (ARDL) model to show that the regional factor in Asia, estimated from the dynamic latent factor model, is mainly explained by Chinese economic variables. More particularly, our results highlight that the bilateral exchange rate of China, both the onshore and the offshore rates, and the macroeconomic climate in China greatly influence the regional factor in Asia in the long-run. These results give some evidence of a Renminbi zone in the long-run and are robust to the inclusion of two other major currencies in Asia, the Japanese Yen and the Korean Won, notably in the long run.
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Suggested Citation

  • Raphael Chiappini & Delphine Lahet, 2020. "Exchange rate movements in emerging economies - Global vs regional factors in Asia," Post-Print hal-03431453, HAL.
  • Handle: RePEc:hal:journl:hal-03431453
    DOI: 10.1016/j.chieco.2019.101386
    Note: View the original document on HAL open archive server: https://hal.science/hal-03431453
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    3. Zuzana Rowland & George Lazaroiu & Ivana Podhorská, 2020. "Use of Neural Networks to Accommodate Seasonal Fluctuations When Equalizing Time Series for the CZK/RMB Exchange Rate," Risks, MDPI, vol. 9(1), pages 1-21, December.
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    5. Keddad, Benjamin & Sato, Kiyotaka, 2022. "The influence of the renminbi and its macroeconomic determinants: A new Chinese monetary order in Asia?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).

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    JEL classification:

    • 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
    • F15 - International Economics - - Trade - - - Economic Integration
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration

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