IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v62y2019icp507-514.html
   My bibliography  Save this article

Time-varying effects of international copper price shocks on China's producer price index

Author

Listed:
  • Wen, Fenghua
  • Zhao, Cong
  • Hu, Chunyan

Abstract

As China becomes the largest international copper importer, we hypothesize that international copper price shocks affect China's producer price index (PPI). To test the hypothesis, we rely on a time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model to analyze the impact of the copper price shock, which is categorized into copper supply shock, aggregate demand shock and copper-specific demand shock. Our results indicate that the impact of international copper price shocks on China's PPI is time-varying. Copper price shocks significantly affect China's PPI over the short and medium terms and the aggregate demand shock displays the most. Also, copper price shocks show greater impact on the production materials PPI than on the living materials PPI.

Suggested Citation

  • Wen, Fenghua & Zhao, Cong & Hu, Chunyan, 2019. "Time-varying effects of international copper price shocks on China's producer price index," Resources Policy, Elsevier, vol. 62(C), pages 507-514.
  • Handle: RePEc:eee:jrpoli:v:62:y:2019:i:c:p:507-514
    DOI: 10.1016/j.resourpol.2018.10.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420718302952
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.resourpol.2018.10.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    2. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    3. Cevik, Serhan & Saadi Sedik, Tahsin, 2014. "A Barrel of Oil or a Bottle of Wine: How Do Global Growth Dynamics Affect Commodity Prices?," Journal of Wine Economics, Cambridge University Press, vol. 9(1), pages 34-50, May.
    4. Gao, Liping & Kim, Hyeongwoo & Saba, Richard, 2014. "How do oil price shocks affect consumer prices?," Energy Economics, Elsevier, vol. 45(C), pages 313-323.
    5. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    6. Lucas Fievet & Didier Sornette, 2018. "Calibrating emergent phenomena in stock markets with agent based models," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    7. Hooker, Mark A, 2002. "Are Oil Shocks Inflationary? Asymmetric and Nonlinear Specifications versus Changes in Regime," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 540-561, May.
    8. Fenghua Wen & Jihong Xiao & Chuangxia Huang & Xiaohua Xia, 2018. "Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 319-334, January.
    9. Wen, Fenghua & Ye, Zhengke & Yang, Huaidong & Li, Ke, 2018. "Exploring the rebound effect from the perspective of household: An analysis of China's provincial level," Energy Economics, Elsevier, vol. 75(C), pages 345-356.
    10. Cunado, Juncal & Jo, Soojin & Perez de Gracia, Fernando, 2015. "Macroeconomic impacts of oil price shocks in Asian economies," Energy Policy, Elsevier, vol. 86(C), pages 867-879.
    11. Fenghua Wen & Zhifang He & Xu Gong & Aiming Liu, 2014. "Investors’ Risk Preference Characteristics Based on Different Reference Point," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-9, April.
    12. 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.
    13. Chen, Shiu-Sheng, 2009. "Oil price pass-through into inflation," Energy Economics, Elsevier, vol. 31(1), pages 126-133, January.
    14. Gao, Liping & Kim, Hyeongwoo & Saba, Richard, 2013. "How Does the Oil Price Shock Affect Consumers?," MPRA Paper 49565, University Library of Munich, Germany.
    15. Marc Gronwald, 2012. "Oil and the U.S. Macroeconomy: A Reinvestigation Using Rolling Impulse Responses," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    16. Darby, Michael R, 1982. "The Price of Oil and World Inflation and Recession," American Economic Review, American Economic Association, vol. 72(4), pages 738-751, September.
    17. Christiane Baumeister & Gert Peersman, 2013. "Time-Varying Effects of Oil Supply Shocks on the US Economy," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(4), pages 1-28, October.
    18. Cashin, Paul & Mohaddes, Kamiar & Raissi, Maziar & Raissi, Mehdi, 2014. "The differential effects of oil demand and supply shocks on the global economy," Energy Economics, Elsevier, vol. 44(C), pages 113-134.
    19. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    20. Robert B. Barsky & Lutz Kilian, 2002. "Do We Really Know That Oil Caused the Great Stagflation? A Monetary Alternative," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 137-198, National Bureau of Economic Research, Inc.
    21. 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.
    22. Svedberg, Peter & Tilton, John E., 2011. "Long-term trends in the Real real prices of primary commodities: Inflation bias and the Prebisch-Singer hypothesis," Resources Policy, Elsevier, vol. 36(1), pages 91-93, March.
    23. Zhujia Yin & Lijuan Liu & Haidong Wang & Fengming Wen, 2018. "Study on the ownership balance and the efficiency of mixed ownership enterprises from the perspective of heterogeneous shareholders," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-15, April.
    24. Álvarez, Luis J. & Hurtado, Samuel & Sánchez, Isabel & Thomas, Carlos, 2011. "The impact of oil price changes on Spanish and euro area consumer price inflation," Economic Modelling, Elsevier, vol. 28(1), pages 422-431.
    25. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    26. Gong, Xu & Lin, Boqiang, 2017. "Forecasting the good and bad uncertainties of crude oil prices using a HAR framework," Energy Economics, Elsevier, vol. 67(C), pages 315-327.
    27. Lance J. Bachmeier & Inkyung Cha, 2011. "Why Don’t Oil Shocks Cause Inflation? Evidence from Disaggregate Inflation Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(6), pages 1165-1183, September.
    28. John T Cuddington & Daniel Jerrett, 2008. "Super Cycles in Real Metals Prices?," IMF Staff Papers, Palgrave Macmillan, vol. 55(4), pages 541-565, December.
    29. Dai, Zhifeng & Wen, Fenghua, 2018. "Some improved sparse and stable portfolio optimization problems," Finance Research Letters, Elsevier, vol. 27(C), pages 46-52.
    30. Juncal Cunado & Soojin Jo & Fernando Perez de Gracia, 2015. "Revisiting the Macroeconomic Impact of Oil Shocks in Asian Economies," Staff Working Papers 15-23, Bank of Canada.
    31. Ana Gómez-Loscos & Mar𨀠 Dolores Gadea & Antonio Montañ鳠, 2012. "Economic growth, inflation and oil shocks: are the 1970s coming back?," Applied Economics, Taylor & Francis Journals, vol. 44(35), pages 4575-4589, December.
    32. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    33. Mansor H. Ibrahim & Kanokwan Chancharoenchai, 2014. "How inflationary are oil price hikes? A disaggregated look at Thailand using symmetric and asymmetric cointegration models," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 19(3), pages 409-422, July.
    34. Gong, Xu & Lin, Boqiang, 2018. "Time-varying effects of oil supply and demand shocks on China's macro-economy," Energy, Elsevier, vol. 149(C), pages 424-437.
    35. Fernandez, Viviana, 2014. "Linear and non-linear causality between price indices and commodity prices," Resources Policy, Elsevier, vol. 41(C), pages 40-51.
    36. Min Zhou & Xiaoqun Liu & Bin Pan & Xin Yang & Fenghua Wen & Xiaohua Xia, 2017. "Effect of Tourism Building Investments on Tourist Revenues in China: A Spatial Panel Econometric Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(9), pages 1973-1987, September.
    37. Sek, Siok Kun, 2017. "Impact of oil price changes on domestic price inflation at disaggregated levels: Evidence from linear and nonlinear ARDL modeling," Energy, Elsevier, vol. 130(C), pages 204-217.
    38. Herwartz, Helmut & Plödt, Martin, 2016. "The macroeconomic effects of oil price shocks: Evidence from a statistical identification approach," Journal of International Money and Finance, Elsevier, vol. 61(C), pages 30-44.
    39. Xiao, Jihong & Zhou, Min & Wen, Fengming & Wen, Fenghua, 2018. "Asymmetric impacts of oil price uncertainty on Chinese stock returns under different market conditions: Evidence from oil volatility index," Energy Economics, Elsevier, vol. 74(C), pages 777-786.
    40. Chen, Mei-Hsiu, 2010. "Understanding world metals prices--Returns, volatility and diversification," Resources Policy, Elsevier, vol. 35(3), pages 127-140, September.
    41. 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.
    42. Fernandez, Viviana, 2012. "Trends in real commodity prices: How real is real?," Resources Policy, Elsevier, vol. 37(1), pages 30-47.
    43. Reboredo, Juan C. & Ugolini, Andrea, 2016. "The impact of downward/upward oil price movements on metal prices," Resources Policy, Elsevier, vol. 49(C), pages 129-141.
    44. Mutafoglu, Takvor H. & Tokat, Ekin & Tokat, Hakki A., 2012. "Forecasting precious metal price movements using trader positions," Resources Policy, Elsevier, vol. 37(3), pages 273-280.
    45. Hongwei Zhang & Xuehong Zhu & Yaoqi Guo & Haibo Liu, 2018. "A separate reduced‐form volatility forecasting model for nonferrous metal market: Evidence from copper and aluminum," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 754-766, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Yingli & Huang, Jianbai & Chen, Jinyu, 2021. "Dynamic spillovers of geopolitical risks and gold prices: New evidence from 18 emerging economies," Resources Policy, Elsevier, vol. 70(C).
    2. Qin, Yun & Chen, Jinyu & Dong, Xuesong, 2021. "Oil prices, policy uncertainty and travel and leisure stocks in China," Energy Economics, Elsevier, vol. 96(C).
    3. Yufeng CHEN & Shuo YANG, 2022. "How Does the Reform in Pricing Mechanism Affect the World’s Iron Ore Price: A Time-Varying Parameter SVAR Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 83-103, April.
    4. Chen, Jinyu & Zhu, Xuehong & Li, Hailing, 2020. "The pass-through effects of oil price shocks on China's inflation: A time-varying analysis," Energy Economics, Elsevier, vol. 86(C).
    5. Chen, Yufeng & Yang, Shuo, 2021. "Time-varying effect of international iron ore price on China’s inflation: A complete price chain with TVP-SVAR-SV model," Resources Policy, Elsevier, vol. 73(C).
    6. Ding, Shusheng & Wang, Kaihao & Cui, Tianxiang & Du, Min, 2023. "The time-varying impact of geopolitical risk on natural resource prices: The post-COVID era evidence," Resources Policy, Elsevier, vol. 86(PB).
    7. Ding, Qian & Huang, Jianbai & Chen, Jinyu & Luo, Xianfeng, 2024. "Climate warming, renewable energy consumption and rare earth market: Evidence from the United States," Energy, Elsevier, vol. 290(C).
    8. Zhou, Ying-Zhe & Huang, Jian-Bai & Chen, Jin-Yu, 2019. "Time-varying effect of the financialization of nonferrous metals markets on China's industrial sector," Resources Policy, Elsevier, vol. 64(C).
    9. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2020. "The effects of geopolitical risks on the stock dynamics of China's rare metals: A TVP-VAR analysis," Resources Policy, Elsevier, vol. 68(C).
    10. Jinyu Chen & Xuehong Zhu, 2021. "The Effects of Different Types of Oil Price Shocks on Industrial PPI: Evidence from 36 Sub-industries in China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(12), pages 3411-3434, September.
    11. Sun, Xiaotian & Fang, Wei & Gao, Xiangyun & An, Sufang & Liu, Siyao & Wu, Tao, 2021. "Time-varying causality inference of different nickel markets based on the convergent cross mapping method," Resources Policy, Elsevier, vol. 74(C).
    12. Huang, Jianbai & Dong, Xuesong & Chen, Jinyu & Zhong, Meirui, 2022. "Do oil prices and economic policy uncertainty matter for precious metal returns? New insights from a TVP-VAR framework," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 433-445.
    13. Wei, Jiangqiao & Ma, Zhe & Wang, Anjian & Li, Pengyuan & Sun, Xiaoyan & Yuan, Xiaojing & Hao, Hongchang & Jia, Hongxiang, 2022. "Multiscale nonlinear Granger causality and time-varying effect analysis of the relationship between iron ore futures and spot prices," Resources Policy, Elsevier, vol. 77(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gong, Xu & Lin, Boqiang, 2018. "Time-varying effects of oil supply and demand shocks on China's macro-economy," Energy, Elsevier, vol. 149(C), pages 424-437.
    2. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
    3. Chen, Jinyu & Zhu, Xuehong & Li, Hailing, 2020. "The pass-through effects of oil price shocks on China's inflation: A time-varying analysis," Energy Economics, Elsevier, vol. 86(C).
    4. Jin‐Yu Chen & Xue‐Hong Zhu & Mei‐Rui Zhong, 2021. "Time‐varying effects and structural change of oil price shocks on industrial output: Evidence from China's oil industrial chain," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3460-3472, July.
    5. Li, Wenlan & Cheng, Yuxiang & Fang, Qiang, 2020. "Forecast on silver futures linked with structural breaks and day-of-the-week effect," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    6. Zhu, Xuehong & Liao, Jianhui & Chen, Ying, 2021. "Time-varying effects of oil price shocks and economic policy uncertainty on the nonferrous metals industry: From the perspective of industrial security," Energy Economics, Elsevier, vol. 97(C).
    7. Jinyu Chen & Xuehong Zhu, 2021. "The Effects of Different Types of Oil Price Shocks on Industrial PPI: Evidence from 36 Sub-industries in China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(12), pages 3411-3434, September.
    8. Gong, Xu & Chen, Liqiang & Lin, Boqiang, 2020. "Analyzing dynamic impacts of different oil shocks on oil price," Energy, Elsevier, vol. 198(C).
    9. Liu, Renren & Chen, Jianzhong & Wen, Fenghua, 2021. "The nonlinear effect of oil price shocks on financial stress: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    10. Xiao, Jihong & Hu, Chunyan & Ouyang, Guangda & Wen, Fenghua, 2019. "Impacts of oil implied volatility shocks on stock implied volatility in China: Empirical evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 80(C), pages 297-309.
    11. Wen, Fenghua & Wu, Nan & Gong, Xu, 2020. "China's carbon emissions trading and stock returns," Energy Economics, Elsevier, vol. 86(C).
    12. Zakaria, Muhammad & Khiam, Shahzeb & Mahmood, Hamid, 2021. "Influence of oil prices on inflation in South Asia: Some new evidence," Resources Policy, Elsevier, vol. 71(C).
    13. Youshu Li & Junjie Guo, 2022. "The asymmetric impacts of oil price and shocks on inflation in BRICS: a multiple threshold nonlinear ARDL model," Applied Economics, Taylor & Francis Journals, vol. 54(12), pages 1377-1395, March.
    14. Zhou, Ying-Zhe & Huang, Jian-Bai & Chen, Jin-Yu, 2019. "Time-varying effect of the financialization of nonferrous metals markets on China's industrial sector," Resources Policy, Elsevier, vol. 64(C).
    15. Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
    16. Xie, Nan & Wang, Zongrun & Chen, Sicen & Gong, Xu, 2019. "Forecasting downside risk in China’s stock market based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 530-541.
    17. Rufei Zhang & Haizhen Zhang & Wang Gao & Ting Li & Shixiong Yang, 2022. "The Dynamic Effects of Oil Price Shocks on Exchange Rates—From a Time-Varying Perspective," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    18. Liu, Hong & Wang, Chang & Tian, Meiyu & Wen, Fenghua, 2019. "Analysis of regional difference decomposition of changes in energy consumption in China during 1995–2015," Energy, Elsevier, vol. 171(C), pages 1139-1149.
    19. Xiao, Jihong & Wen, Fenghua & He, Zhifang, 2023. "Impact of geopolitical risks on investor attention and speculation in the oil market: Evidence from nonlinear and time-varying analysis," Energy, Elsevier, vol. 267(C).
    20. Yang, Cai & Gong, Xu & Zhang, Hongwei, 2019. "Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect," Resources Policy, Elsevier, vol. 61(C), pages 548-563.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:62:y:2019:i:c:p:507-514. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.