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Exchange Rate Movements and Fundamentals: Impact of Oil Prices and China¡¯s Growth

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Listed:
  • Shuo Cao

    (Shenzhen Stock Exchange)

  • Hongyi Chen

    (Hong Kong Institute for Monetary Research)

Abstract

This paper identifies five factors that can capture 95% of the variance across 39 US dollar exchange rates based on the principal component method. A time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model is used to analyze the determinants of movements in these exchange rates, revealing that impact of global oil prices and China¡¯s growth has increased significantly since 2008. In particular, shocks to these two fundamentals drive the movements of both commodity and non-commodity currencies recently. The impact of monetary policy shocks on the currency pairs is comparatively small.

Suggested Citation

  • Shuo Cao & Hongyi Chen, 2017. "Exchange Rate Movements and Fundamentals: Impact of Oil Prices and China¡¯s Growth," Working Papers 042017, Hong Kong Institute for Monetary Research.
    • Handle: RePEc:hkm:wpaper:042017
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    References listed on IDEAS

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    1. Charles Engel & Kenneth D. West, 2005. "Exchange Rates and Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 113(3), pages 485-517, June.
    2. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1145-1194.
    3. Jing Cynthia Wu & Fan Dora Xia, 2016. "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 253-291, March.
    4. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    5. Anna Pavlova & Roberto Rigobon, 2007. "Asset Prices and Exchange Rates," The Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1139-1180.
    6. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    7. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    8. Libo Yin & Liyan Han, 2016. "Macroeconomic impacts on commodity prices: China vs. the United States," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 489-500, March.
    9. Hummels, David, 2011. "Robert C. Feenstra and Shang-Jin Wei, Editors, China's Growing Role in World Trade, The University of Chicago Press (2010)," Journal of International Economics, Elsevier, vol. 83(1), pages 92-93, January.
    10. Chang, Yoosoon & Isaac Miller, J. & Park, Joon Y., 2009. "Extracting a common stochastic trend: Theory with some applications," Journal of Econometrics, Elsevier, vol. 150(2), pages 231-247, June.
    11. Sarno, Lucio & Valente, Giorgio, 2005. "Empirical exchange rate models and currency risk: some evidence from density forecasts," Journal of International Money and Finance, Elsevier, vol. 24(2), pages 363-385, March.
    12. Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
    13. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
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