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When prices spike: Identifying excessive volatility in fertilizer markets

Author

Listed:
  • Feng Yao

    (West Virginia University)

  • Manuel A. Hernandez

    (IFPRI)

Abstract

Sharp and volatile fertilizer price movements can hinder adoption and reduce agricultural productivity, especially among vulnerable smallholders. Using a nonparametric location-scale approach to model price returns, we quantify the conditional value-at-risk (CVaR) - the high return threshold exceeded with low probability - to identify excessive price spikes in potash, urea, and di-ammonium phosphate (DAP) markets. We use the bias-corrected estimator from Martins-Filho et al. (2018) and propose a simpler estimator based on Hill (1975). Backtesting results indicate superior performance of the Hill-based estimator, supporting its value as a convenient method for detecting unusual fertilizer price surges amid recurring global volatility.

Suggested Citation

  • Feng Yao & Manuel A. Hernandez, 2026. "When prices spike: Identifying excessive volatility in fertilizer markets," Working Papers 26-02, Department of Economics, West Virginia University.
    • Handle: RePEc:wvu:wpaper:26-02
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    File URL: https://researchrepository.wvu.edu/cgi/viewcontent.cgi?article=1258&context=econ_working-papers
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    References listed on IDEAS

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    1. repec:fpr:gsspwp:162957 is not listed on IDEAS
    2. Manuel A. Hernandez & Maximo Torero, 2013. "Market concentration and pricing behavior in the fertilizer industry: a global approach," Agricultural Economics, International Association of Agricultural Economists, vol. 44(6), pages 723-734, November.
    3. Manuel A. Hernandez & Francisco Ceballos & Maria Lucia Berrospi & Viviana M. E. Perego & Melissa Brown & Elena Mora Lopez, 2026. "Price and Volatility Transmission From International to Domestic Food and Fertilizer Markets in Central America," Agricultural Economics, International Association of Agricultural Economists, vol. 57(1), January.
    4. Oliver B. Linton & Yang Yan, 2011. "Semi- and Nonparametric ARCH Processes," Journal of Probability and Statistics, Hindawi, vol. 2011, pages 1-17, August.
    5. Li, Shuo & Peng, Liuhua & Song, Xiaojun, 2023. "Simultaneous Confidence Bands For Conditional Value-At-Risk And Expected Shortfall," Econometric Theory, Cambridge University Press, vol. 39(5), pages 1009-1043, October.
    6. Yannick Hoga, 2019. "Confidence Intervals for Conditional Tail Risk Measures in ARMA–GARCH Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 613-624, October.
    7. Hernandez, Manuel A. & Torero, Máximo, 2018. "Promoting competition in the fertilizer industry in Africa: A global and local approach," Issue briefs 978-089629-341-0, International Food Policy Research Institute (IFPRI).
    8. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2015. "High-Order Conditional Quantile Estimation Based on Nonparametric Models of Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 907-958, December.
    9. Martins-Filho, Carlos & Yao, Feng & Torero, Maximo, 2018. "Nonparametric Estimation Of Conditional Value-At-Risk And Expected Shortfall Based On Extreme Value Theory," Econometric Theory, Cambridge University Press, vol. 34(1), pages 23-67, February.
    10. Martins-Filho, Carlos & Yao, Feng, 2008. "A smooth nonparametric conditional quantile frontier estimator," Journal of Econometrics, Elsevier, vol. 143(2), pages 317-333, April.
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    • C - Mathematical and Quantitative Methods

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