IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i10p7755-d1142523.html
   My bibliography  Save this article

The Fluctuation Characteristics and Periodic Patterns of Potato Prices in China

Author

Listed:
  • Hongwei Lu

    (Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Tingting Li

    (Institute of Agricultural Economy and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Jianfei Lv

    (Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Aoxue Wang

    (Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Qiyou Luo

    (Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Mingjie Gao

    (Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Guojing Li

    (Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

Abstract

The aim of this paper was to provide a more scientific and effective analysis of the fluctuation pattern of the Chinese potato market by extracting the characteristics of the price fluctuation cycle to effectively grasp the characteristics of price changes in the potato market, thus promoting the stable and healthy development of the Chinese potato industry, and to expand the application scenarios of the EEMD model to provide a reference for the study of price fluctuation patterns in other agricultural markets. This study used an ensemble empirical modal decomposition (EEMD) model to examine time-series data on Chinese wholesale potato market prices from January 2005 to December 2021. The results showed that (1) Chinese wholesale potato market prices are characterized by some rigidity, with sharp changes in growth rates; (2) Chinese wholesale potato market prices are dominated by short- and medium-term fluctuations, and the decomposed components can better reflect the characteristics of the original series fluctuations; (3) Chinese wholesale potato market monthly prices have long- and short-term fluctuations with a 6- and 19-month cycle, and are dominated by short-term high-frequency fluctuations; (4) monthly price fluctuations in the Chinese wholesale potato market are more intense in high-frequency than low-frequency fluctuations, and there is a strong correlation between high- and low-frequency fluctuations in precipitation, temperature and potato prices. Finally, suggestions were made for creating and improving a national potato price information platform and strengthening the information early warning mechanism; improving the potato production interest linkage mechanism and enhancing potato farmers’ ability to cope with market and natural risks; and improving the potato reserve system and potato storage facilities.

Suggested Citation

  • Hongwei Lu & Tingting Li & Jianfei Lv & Aoxue Wang & Qiyou Luo & Mingjie Gao & Guojing Li, 2023. "The Fluctuation Characteristics and Periodic Patterns of Potato Prices in China," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:7755-:d:1142523
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/10/7755/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/10/7755/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ceballos, Francisco & Hernandez, Manuel A. & Minot, Nicholas & Robles, Miguel, 2017. "Grain Price and Volatility Transmission from International to Domestic Markets in Developing Countries," World Development, Elsevier, vol. 94(C), pages 305-320.
    2. María Bielza & Alberto Garrido & José M. Sumpsi, 2007. "Finding optimal price risk management instruments: the case of the Spanish potato sector," Agricultural Economics, International Association of Agricultural Economists, vol. 36(1), pages 67-78, January.
    3. Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
    4. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    5. David A. Hennessy, 1998. "The Production Effects of Agricultural Income Support Policies under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 46-57.
    6. Grabowski, Richard & Self, Sharmistha, 2016. "Staple food price instability and structural change: Indonesian experience," Journal of Asian Economics, Elsevier, vol. 47(C), pages 35-44.
    7. Mao, Xuegeng & Yang, Albert C. & Peng, Chung-Kang & Shang, Pengjian, 2020. "Analysis of economic growth fluctuations based on EEMD and causal decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    8. Headey, Derek, 2011. "Rethinking the global food crisis: The role of trade shocks," Food Policy, Elsevier, vol. 36(2), pages 136-146, April.
    9. Marc F. Bellemare, 2015. "Rising Food Prices, Food Price Volatility, and Social Unrest," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 1-21.
    10. Xingchen Lv & Jun Meng & Qiufeng Wu, 2022. "Dynamic Influence of Network Public Opinions on Price Fluctuation of Small Agricultural Products Based on NLP-TVP-VAR Model—Taking Garlic as an Example," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    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. Rui-Feng Wang & Wen-Hao Su, 2024. "The Application of Deep Learning in the Whole Potato Production Chain: A Comprehensive Review," Agriculture, MDPI, vol. 14(8), pages 1-30, July.

    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. Kalle Hirvonen & Bart Minten & Belay Mohammed & Seneshaw Tamru, 2021. "Food prices and marketing margins during the COVID‐19 pandemic: Evidence from vegetable value chains in Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 52(3), pages 407-421, May.
    2. Edward Knapp & Jason Loughrey, 2017. "The single farm payment and income risk in Irish farms 2005–2013," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 5(1), pages 1-15, December.
    3. Yamauchi, Futoshi & Larson, Donald F., 2019. "Long-term impacts of an unanticipated spike in food prices on child growth in Indonesia," World Development, Elsevier, vol. 113(C), pages 330-343.
    4. Bradford, Scott C. & Negi, Digvijay Singh & Ramaswami, Bharat, 2022. "International risk sharing for food staples," Journal of Development Economics, Elsevier, vol. 158(C).
    5. Nakelse, Tebila & Dalton, Timothy J. & Hendricks, Nathan P. & Hodjo, Manzamasso, 2018. "Are smallholder farmers better or worse off from an increase in the international price of cereals?," Food Policy, Elsevier, vol. 79(C), pages 213-223.
    6. Pierre-Emmanuel Darpeix, 2019. "Literature review on the consequences of food price spikes and price volatility," Working Papers hal-02072329, HAL.
    7. Zhuo Chen & Bo Yan, 2022. "The impact of trade policy on soybean futures in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(4), pages 1152-1163, June.
    8. Zhuo Chen & Bo Yan & Hanwen Kang, 2023. "Price bubbles of agricultural commodities: evidence from China’s futures market," Empirical Economics, Springer, vol. 64(1), pages 195-222, January.
    9. Hualin Xie & Bohao Wang, 2017. "An Empirical Analysis of the Impact of Agricultural Product Price Fluctuations on China’s Grain Yield," Sustainability, MDPI, vol. 9(6), pages 1-14, May.
    10. An, Henry & Qiu, Feng & Zheng, Yanan, 2016. "How do export controls affect price transmission and volatility spillovers in the Ukrainian wheat and flour markets?," Food Policy, Elsevier, vol. 62(C), pages 142-150.
    11. Renzaho, Andre M.N. & Kamara, Joseph K. & Toole, Michael, 2017. "Biofuel production and its impact on food security in low and middle income countries: Implications for the post-2015 sustainable development goals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 503-516.
    12. Gutierrez, L. & Piras, F., 2013. "A Global Wheat Market Model (GLOWMM) for the Analysis of Wheat Export Prices," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149760, Italian Association of Agricultural and Applied Economics (AIEAA).
    13. Shuai Liu & Dingyu Liu & Sibo Ge, 2024. "Impact of external shocks on international corn price fluctuations," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(1), pages 1-11.
    14. Pierre-Emmanuel Darpeix, 2019. "Literature review on the consequences of food price spikes and price volatility," PSE Working Papers hal-02072329, HAL.
    15. Bernardina Algieri, 2021. "Fast & furious: Do psychological and legal factors affect commodity price volatility?," The World Economy, Wiley Blackwell, vol. 44(4), pages 980-1017, April.
    16. Aled W. Jones & Alexander Phillips, 2016. "Historic Food Production Shocks: Quantifying the Extremes," Sustainability, MDPI, vol. 8(5), pages 1-10, April.
    17. Matthias Kalkuhl & Mekbib Haile & Lukas Kornher & Marta Kozicka, 2015. "Cost-benefit framework for policy action to navigate food price spikes. FOODSECURE Working Paper No 33," FOODSECURE Working papers 33, LEI Wageningen UR.
    18. David R Just, 2023. "On the policy relevance of agricultural economics," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(4), pages 1256-1276.
    19. Xu, Chao & Zhao, Xiaojun & Wang, Yanwen, 2022. "Causal decomposition on multiple time scales: Evidence from stock price-volume time series," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    20. Guo, Jin & Tanaka, Tetsuji, 2022. "Do biofuel production and financial speculation in agricultural commodities influence African food prices? New evidence from a TVP-VAR extended joint connectedness approach," Energy Economics, Elsevier, vol. 116(C).

    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:jsusta:v:15:y:2023:i:10:p:7755-:d:1142523. 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.