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Time-varying monetary policy shocks and the dynamics of Chinese commodity prices

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Listed:
  • Lyu, Yongjian
  • Yi, Heling
  • Cao, Jin
  • Yang, Mo

Abstract

With the trading volume and openness of the Chinese commodity futures market being developed substantially in recent years, this paper explores the effects of Chinese monetary policy shocks on the dynamics of commodity futures prices under dynamic structural changes by imposing reduced constraints. The results show the following: (1) Monetary policy shocks are fundamental triggers for price changes in most Chinese commodity futures market indices and positive monetary policy shocks significantly push up both aggregate market indices and some sectoral market indices. (2) Commodity sectors have heterogeneous reactions to monetary policy shocks. For example, unlike other commodity sectors, grain is barely affected by monetary policy shocks, which may be due to price regulation of agricultural products and low levels of sector financialization. (3) The relationship between monetary policy shocks and price changes in commodity futures markets is time-varyingly dependent on the economic environment. In particular, the impulse responses for most of the commodity futures market indices tend to be larger during the global financial crisis period, then gradually declined from 2009.

Suggested Citation

  • Lyu, Yongjian & Yi, Heling & Cao, Jin & Yang, Mo, 2022. "Time-varying monetary policy shocks and the dynamics of Chinese commodity prices," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:pacfin:v:75:y:2022:i:c:s0927538x22001317
    DOI: 10.1016/j.pacfin.2022.101836
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    as
    1. Kilian, Lutz & Lee, Thomas K., 2014. "Quantifying the speculative component in the real price of oil: The role of global oil inventories," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 71-87.
    2. Leeper, Eric M. & Zha, Tao, 2003. "Modest policy interventions," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1673-1700, November.
    3. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425, June.
    4. Leippold, Markus & Wang, Qian & Zhou, Wenyu, 2022. "Machine learning in the Chinese stock market," Journal of Financial Economics, Elsevier, vol. 145(2), pages 64-82.
    5. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2015. "US monetary policy and sectoral commodity prices," Journal of International Money and Finance, Elsevier, vol. 57(C), pages 61-85.
    6. Christiane Baumeister & Gert Peersman, 2013. "The Role Of Time‐Varying Price Elasticities In Accounting For Volatility Changes In The Crude Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1087-1109, November.
    7. Jia, Rui-Lin & Wang, Dong-Hua & Tu, Jing-Qing & Li, Sai-Ping, 2016. "Correlation between agricultural markets in dynamic perspective—Evidence from China and the US futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 83-92.
    8. repec:dau:papers:123456789/14980 is not listed on IDEAS
    9. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    10. Hyunju Kang & Bok-Keun Yu & Jongmin Yu, 2016. "Global Liquidity and Commodity Prices," Review of International Economics, Wiley Blackwell, vol. 24(1), pages 20-36, February.
    11. A. Anzuini & M. J. Lombardi & P. Pagano, 2013. "The Impact of Monetary Policy Shocks on Commodity Prices," International Journal of Central Banking, International Journal of Central Banking, vol. 9(3), pages 125-150, September.
    12. Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 869-889, August.
    13. Markku Lanne & Henri Nyberg, 2016. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 595-603, August.
    14. Creti, Anna & Joëts, Marc & Mignon, Valérie, 2013. "On the links between stock and commodity markets' volatility," Energy Economics, Elsevier, vol. 37(C), pages 16-28.
    15. Ratti, Ronald A. & Vespignani, Joaquin L., 2013. "Crude oil prices and liquidity, the BRIC and G3 countries," Energy Economics, Elsevier, vol. 39(C), pages 28-38.
    16. Bouri, Elie & Chen, Qian & Lien, Donald & Lv, Xin, 2017. "Causality between oil prices and the stock market in China: The relevance of the reformed oil product pricing mechanism," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 34-48.
    17. Pindyck, Robert S & Rotemberg, Julio J, 1990. "The Excess Co-movement of Commodity Prices," Economic Journal, Royal Economic Society, vol. 100(403), pages 1173-1189, December.
    18. Mr. Reginald Darius, 2010. "Can Global Liquidity Forecast Asset Prices?," IMF Working Papers 2010/196, International Monetary Fund.
    19. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.
    20. Ratti, Ronald A. & Vespignani, Joaquin L., 2015. "Commodity prices and BRIC and G3 liquidity: A SFAVEC approach," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 18-33.
    21. Hervé Ott, 2014. "Extent and possible causes of intrayear agricultural commodity price volatility," Agricultural Economics, International Association of Agricultural Economists, vol. 45(2), pages 225-252, March.
    22. Christiane Baumeister & James D. Hamilton, 2019. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," American Economic Review, American Economic Association, vol. 109(5), pages 1873-1910, May.
    23. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2010. "The macroeconomic determinants of volatility in precious metals markets," Resources Policy, Elsevier, vol. 35(2), pages 65-71, June.
    24. Belke, Ansgar H. & Bordon, Ingo G. & Hendricks, Torben W., 2014. "Monetary policy, global liquidity and commodity price dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 1-16.
    25. Hammoudeh, Shawkat & Yuan, Yuan, 2008. "Metal volatility in presence of oil and interest rate shocks," Energy Economics, Elsevier, vol. 30(2), pages 606-620, March.
    26. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    27. Kaiji Chen & Jue Ren & Tao Zha, 2018. "The Nexus of Monetary Policy and Shadow Banking in China," American Economic Review, American Economic Association, vol. 108(12), pages 3891-3936, December.
    28. Marco Del Negro & Giorgio E. Primiceri, 2015. "Time Varying Structural Vector Autoregressions and Monetary Policy: A Corrigendum," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1342-1345.
    29. Liu, Qingfu & An, Yunbi, 2011. "Information transmission in informationally linked markets: Evidence from US and Chinese commodity futures markets," Journal of International Money and Finance, Elsevier, vol. 30(5), pages 778-795, September.
    30. Klotz, Philipp & Lin, Tsoyu Calvin & Hsu, Shih-Hsun, 2014. "Global commodity prices, economic activity and monetary policy: The relevance of China," Resources Policy, Elsevier, vol. 42(C), pages 1-9.
    31. 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.
    32. Belke, Ansgar & Orth, Walter & Setzer, Ralph, 2010. "Liquidity and the dynamic pattern of asset price adjustment: A global view," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1933-1945, August.
    33. Frankel, Jeffrey A., 2014. "Effects of speculation and interest rates in a “carry trade” model of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 88-112.
    34. Lyu, Yongjian & Wei, Yu & Hu, Yingyi & Yang, Mo, 2021. "Good volatility, bad volatility and economic uncertainty: Evidence from the crude oil futures market," Energy, Elsevier, vol. 222(C).
    35. Akram, Q. Farooq, 2009. "Commodity prices, interest rates and the dollar," Energy Economics, Elsevier, vol. 31(6), pages 838-851, November.
    36. Dean Scrimgeour, 2015. "Commodity Price Responses to Monetary Policy Surprises," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 88-102.
    37. Beckmann, Joscha & Belke, Ansgar & Czudaj, Robert, 2014. "Does global liquidity drive commodity prices?," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 224-234.
    38. Shawkat Hammoudeh & Duc Khuong Nguyen & Ricardo M. Sousa, 2014. "China’s Monetary Policy and Commodity Prices," Working Papers 2014-298, Department of Research, Ipag Business School.
    39. Md Rafayet Alam & Scott Gilbert, 2017. "Monetary policy shocks and the dynamics of agricultural commodity prices: evidence from structural and factor†augmented VAR analyses," Agricultural Economics, International Association of Agricultural Economists, vol. 48(1), pages 15-27, January.
    40. Riggi, Marianna & Venditti, Fabrizio, 2015. "The time varying effect of oil price shocks on euro-area exports," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 75-94.
    41. Frankel, Jeffrey A & Hardouvelis, Gikas A, 1985. "Commodity Prices, Money Surprises and Fed Credibility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 17(4), pages 425-438, November.
    42. Ordu, Beyza Mina & Oran, Adil & Soytas, Ugur, 2018. "Is food financialized? Yes, but only when liquidity is abundant," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 82-96.
    43. Triantafyllou, Athanasios & Dotsis, George, 2017. "Option-implied expectations in commodity markets and monetary policy," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 1-17.
    44. Humphreys, David, 2009. "Comment: Unravelling the causes of the mineral price boom," Resources Policy, Elsevier, vol. 34(3), pages 103-104, September.
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    More about this item

    Keywords

    Chinese commodity futures market; Monetary policy; Time-varying impulse responses;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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