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Modelling the Effects of Oil Prices on Global Fertilizer Prices and Volatility

Author

Listed:
  • Ping-Yu Chen

    (Department of Applied Economics, National Chung Hsing University, Taiwan)

  • Chia-Lin Chang

    (Department of Applied Economics, Department of Finance, National Chung Hsing University, Taiwan)

  • Chi-Chung Chen

    (Department of Applied Economics, National Chung Hsing University, Taiwan)

  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute, The Netherlands, Department of Quantitative Economics, Complutense University of Madrid, and Institute of Economic Research, Kyoto University.)

Abstract

The main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, ARDL model, and alternative volatility models, including GARCH, EGARCH, and GJR models, are used to investigate the relationship between crude oil price and six global fertilizer prices. The empirical results from ARDL show that most fertilizer prices are significantly affected by the crude oil price while the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods.

Suggested Citation

  • Ping-Yu Chen & Chia-Lin Chang & Chi-Chung Chen & Michael McAleer, 2013. "Modelling the Effects of Oil Prices on Global Fertilizer Prices and Volatility," Documentos de Trabajo del ICAE 2013-06, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Jan 2013.
    • Handle: RePEc:ucm:doicae:1306
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    References listed on IDEAS

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    Cited by:

    1. David E. Allen & Chialin Chang & Michael McAleer & Abhay K Singh, 2018. "A cointegration analysis of agricultural, energy and bio-fuel spot, and futures prices," Applied Economics, Taylor & Francis Journals, vol. 50(7), pages 804-823, February.
    2. Andre Yone Haughton & Emma M. Iglesias, 2017. "Exchange Rate Movements, Stock Prices and Volatility in the Caribbean and Latin America," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 437-447.
    3. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
    4. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    5. Alamah, Zein & Elgammal, Walid & Fakih, Ali, 2024. "Does twitter economic uncertainty matter for wheat prices?," Economics Letters, Elsevier, vol. 234(C).
    6. Harun Uçak & Yakup Ari & Esin Yelgen, 2022. "The volatility connectedness among fertilisers and agricultural crop prices: Evidence from selected main agricultural products," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(9), pages 348-360.
    7. Khalfaoui, Rabeh & Shahzad, Umer & Ghaemi Asl, Mahdi & Ben Jabeur, Sami, 2023. "Investigating the spillovers between energy, food, and agricultural commodity markets: New insights from the quantile coherency approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 63-80.
    8. Duc Hong Vo & Tan Ngoc Vu & Anh The Vo & Michael McAleer, 2019. "Modeling the Relationship between Crude Oil and Agricultural Commodity Prices," Energies, MDPI, vol. 12(7), pages 1-41, April.
    9. Zhengliang Yang & Xiaoxue Du & Liang Lu & Hernan Tejeda, 2022. "Price and Volatility Transmissions among Natural Gas, Fertilizer, and Corn Markets: A Revisit," JRFM, MDPI, vol. 15(2), pages 1-14, February.

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    More about this item

    Keywords

    Fertilizer Price; Oil Price; Volatility.;
    All these keywords.

    JEL classification:

    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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