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Impact of China on World Commodity Prices and Commodity Exporters

Author

Listed:
  • Arpita Chatterjee

    (UNSW Business School, UNSW)

  • Richa Saraf

    (SUNY-Albany)

Abstract
We study the effect of a domestic shock in China on the real economy and financial markets of a commodity exporting country. We estimate a dynamic factor model using Bayesian methods to identify a China factor and a global factor using monthly macroeconomic data from China and rest of the world. We, then, assess implications of the China factor on global commodity prices and macroeconomy of a commodity exporting nation in a reduced form Bayesian VAR. A negative China shock causes fall in global commodity prices leading to output loss and stock market fall in these countries. China shock affects output of only a subset of countries in our sample compared to US shock, which affects all countries. Stock markets of commodity dependent countries respond strongly and more quickly to China shock than to US shock. China shock also has more persistent effect on commodity prices than US shock.

Suggested Citation

  • Arpita Chatterjee & Richa Saraf, 2017. "Impact of China on World Commodity Prices and Commodity Exporters," Discussion Papers 2017-13, School of Economics, The University of New South Wales.
    • Handle: RePEc:swe:wpaper:2017-13
    as

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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2017-13.pdf
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    References listed on IDEAS

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    1. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224, National Bureau of Economic Research, Inc.
    2. Ludovic Gauvin & Cyril C. Rebillard, 2018. "Towards recoupling? Assessing the global impact of a Chinese hard landing through trade and commodity price channels," The World Economy, Wiley Blackwell, vol. 41(12), pages 3379-3415, December.
    3. M. Ayhan Kose & Eswar S. Prasad & Marco E. Terrones, 2003. "How Does Globalization Affect the Synchronization of Business Cycles?," American Economic Review, American Economic Association, vol. 93(2), pages 57-62, May.
    4. M. Albert & C. Jude & C. Rebillard, 2015. "The Long Landing Scenario: Rebalancing from Overinvestment and Excessive Credit Growth. Implications for Potential Growth in China," Working papers 572, Banque de France.
    5. Fernald, John G. & Spiegel, Mark M. & Swanson, Eric T., 2014. "Monetary policy effectiveness in China: Evidence from a FAVAR model," Journal of International Money and Finance, Elsevier, vol. 49(PA), pages 83-103.
    6. 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.
    7. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    8. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    9. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    10. Arpita Chatterjee, 2014. "Globalization and Monetary Policy Comovement: Evidence from G-7 Countries," Discussion Papers 2014-19, School of Economics, The University of New South Wales.
    11. Erten, Bilge & Ocampo, José Antonio, 2013. "Super Cycles of Commodity Prices Since the Mid-Nineteenth Century," World Development, Elsevier, vol. 44(C), pages 14-30.
    12. Mr. Il Houng Lee & Mr. Murtaza H Syed & Mr. Liu Xueyan, 2012. "Is China Over-Investing and Does it Matter?," IMF Working Papers 2012/277, International Monetary Fund.
    13. Ayhan Kose, M. & Otrok, Christopher & Whiteman, Charles H., 2008. "Understanding the evolution of world business cycles," Journal of International Economics, Elsevier, vol. 75(1), pages 110-130, May.
    14. Ivanov Ventzislav & Kilian Lutz, 2005. "A Practitioner's Guide to Lag Order Selection For VAR Impulse Response Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-36, March.
    15. 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.
    16. Jane Haltmaier, 2013. "Challenges for the future of Chinese economic growth," International Finance Discussion Papers 1072, Board of Governors of the Federal Reserve System (U.S.).
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    Cited by:

    1. Bhattarai, Saroj & Chatterjee, Arpita & Park, Woong Yong, 2020. "Global spillover effects of US uncertainty," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 71-89.

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    More about this item

    Keywords

    China; Commodities; Bayesian VAR; Dynamic Factor Model; Emerging Market Economies;
    All these keywords.

    JEL classification:

    • F62 - International Economics - - Economic Impacts of Globalization - - - Macroeconomic Impacts
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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