IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i8p1343-d1454124.html
   My bibliography  Save this article

The Impact of Pig Futures on the Price Transmission in the Pig Industry Chain during Market Shocks

Author

Listed:
  • Yingman Wang

    (School Finance, Zhongnan University of Economics and Law, Wuhan 430073, China)

  • Yubin Huangfu

    (School Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

Abstract

In recent years, frequent external emergencies have continuously impacted China’s pig industry chain. As the scale and standardization of pig farming in China have increasingly improved, pig futures have met the conditions for good operation and were listed for trading on the Dalian Commodity Exchange on 8 January 2021. To study the impact and influence of African swine fever, COVID-19, and the listing of pig futures on the price transmission mechanism at various stages of China’s pig industry, weekly price data from the pig industry from January 2015 to June 2023 were selected to construct an SV-TVP-VAR model for analysis. The empirical results showed that the shocks of African swine fever and COVID-19 caused price fluctuations at various stages of the pig industry chain, while price fluctuations significantly decreased after the listing of pig futures. Therefore, the introduction of pig futures effectively alleviated the price fluctuations at various stages of the pig industry chain following the shocks of African swine fever and COVID-19, and relevant policy recommendations are proposed accordingly.

Suggested Citation

  • Yingman Wang & Yubin Huangfu, 2024. "The Impact of Pig Futures on the Price Transmission in the Pig Industry Chain during Market Shocks," Agriculture, MDPI, vol. 14(8), pages 1-18, August.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:8:p:1343-:d:1454124
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/8/1343/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/14/8/1343/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Easwaran, R. Salvadi & Ramasundaram, P., 2008. "Whether commodity futures market in agriculture is efficient in price discovery? - An econometric analysis," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 21(Conferenc).
    3. 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.
    4. Colin A. Carter & Sandeep Mohapatra, 2008. "How Reliable Are Hog Futures as Forecasts?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 367-378.
    5. Hachmi Ben Ameur & Zied Ftiti & Waël Louhichi, 2022. "Revisiting the relationship between spot and futures markets: evidence from commodity markets and NARDL framework," Annals of Operations Research, Springer, vol. 313(1), pages 171-189, June.
    6. Param Silvapulle & Imad A. Moosa, 1999. "The relationship between spot and futures prices: Evidence from the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(2), pages 175-193, April.
    7. Arthur A. Harlow, 1960. "The Hog Cycle and the Cobweb Theorem," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 42(4), pages 842-853.
    Full references (including those not matched with items on IDEAS)

    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. Zhang, Zhikai & Wang, Yudong & Xiao, Jihong & Zhang, Yaojie, 2023. "Not all geopolitical shocks are alike: Identifying price dynamics in the crude oil market under tensions," Resources Policy, Elsevier, vol. 80(C).
    2. Coşkun Akdeniz, 2021. "Construction of the Monetary Conditions Index with TVP-VAR Model: Empirical Evidence for Turkish Economy," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 215-228, Springer.
    3. Yang, Xite & Zhang, Qin & Liu, Haiyue & Liu, Zihan & Tao, Qiufan & Lai, Yongzeng & Huang, Linya, 2024. "Economic policy uncertainty, macroeconomic shocks, and systemic risk: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    4. Zhong, Meirui & Zhang, Rui & Ren, Xiaohang, 2023. "The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 123(C).
    5. Tomoyuki Yagi & Yoshiyuki Kurachi & Masato Takahashi & Kotone Yamada & Hiroshi Kawata, 2022. "Pass-Through of Cost-Push Pressures to Consumer Prices," Bank of Japan Working Paper Series 22-E-17, Bank of Japan.
    6. Lu, Man & Wang, Wei & Chen, Fengwen & Li, Hongmei, 2024. "Dynamic impacts of multidimensional uncertainty on the renminbi exchange rate: Insights from time-varying analysis," International Review of Financial Analysis, Elsevier, vol. 94(C).
    7. Shioji, Etsuro, 2015. "Time varying pass-through: Will the yen depreciation help Japan hit the inflation target?," Journal of the Japanese and International Economies, Elsevier, vol. 37(C), pages 43-58.
    8. Robert N. McCauley & Patrick McGuire & Vladyslav Sushko, 2015. "Global dollar credit: links to US monetary policy and leverage," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 30(82), pages 187-229.
    9. Pedro Gomis-Porqueras & Romina Ruprecht & Xuan Zhou, 2023. "A Financial Stress Index for a Small Open Economy: The Australian Case," Finance and Economics Discussion Series 2023-029, Board of Governors of the Federal Reserve System (U.S.).
    10. Jiang, Yanhui & Qu, Bo & Hong, Yun & Xiao, Xiyue, 2024. "Dynamic connectedness of inflation around the world: A time-varying approach from G7 and E7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 111-125.
    11. SASAKI Yuri & YOSHIDA Yushi & Piotr Kansho OTSUBO, 2019. "Exchange rate pass-through on Japanese prices: Import price, producer price, and core CPI," Discussion papers 19078, Research Institute of Economy, Trade and Industry (RIETI).
    12. Xie He & Xiao-Jing Cai & Shigeyuki Hamori, 2018. "Bank Credit and Housing Prices in China: Evidence from a TVP-VAR Model with Stochastic Volatility," JRFM, MDPI, vol. 11(4), pages 1-16, December.
    13. Xiaoqing An & William A. Barnett & Xue Wang & Qingyuan Wu, 2023. "Brexit spillovers: how economic policy uncertainty affects foreign direct investment and international trade," The European Journal of Finance, Taylor & Francis Journals, vol. 29(16), pages 1913-1932, November.
    14. Guangyang Chen & Kai Dong & Shaonan Wang & Xiuli Du & Ronghua Zhou & Zhongwei Yang, 2022. "The Dynamic Relationship among Bank Credit, House Prices and Carbon Dioxide Emissions in China," IJERPH, MDPI, vol. 19(16), pages 1-18, August.
    15. Sheng Zhu & Ella Kavanagh & Niall O'Sullivan, 2021. "Constructing a financial conditions index for the United Kingdom: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2976-2989, April.
    16. Feng, Huiqun & Zhang, Jun & Guo, Na, 2023. "Time-varying linkages between energy and stock markets: Dynamic spillovers and driving factors," International Review of Financial Analysis, Elsevier, vol. 89(C).
    17. 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).
    18. Kansho Piotr Otsubo, 2018. "The Effects of Fiscal and Monetary Policies in Japan: What Combination of Policies Should Be Used?," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 9(01n02), pages 1-25, February.
    19. Liang Xie & Xianzhong Mu & Kuanyuting Lu & Dongou Hu & Guangwen Hu, 2023. "The time-varying relationship between CO2 emissions, heterogeneous energy consumption, and economic growth in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 7769-7793, August.
    20. Kang, Sang Hoon & Islam, Faridul & Kumar Tiwari, Aviral, 2019. "The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 90-101.

    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:gam:jagris:v:14:y:2024:i:8:p:1343-:d:1454124. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.