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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
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2017-13.pdf
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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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    Keywords

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    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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