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The linkage between oil and agricultural commodity prices in the light of the perceived global risk

Author

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  • Giray GOZGOR

    (Department of Economics and Finance, Dogus University, Istanbul, Turkey)

  • Baris KABLAMACI

    (Department of Economics, Istanbul University, Istanbul, Turkey)

Abstract

The paper examines a systematic interrelationship between the world oil and agricultural commodity prices, taking the role of the USD and the perceived global market risks into consideration for the period from January 1990 to June 2013. The authors initially determine the significant cross-sectional dependence in a large balanced panel framework for 27 commodity prices, and then apply the second generation panel unit root (PUR) tests. Findings from the PUR tests clearly suggest that there is a strong unit root in agricultural commodity prices. In addition, the empirical findings from the fixed effects panel data, panel co-integration analysis, the Panel-Wald Causality tests, and the common correlated effects mean group estimations strongly show that the world oil price and the weak USD have positive impacts on almost all agricultural commodity prices. There are also retained the adjuvant effects of the escalatory perceived global market risk upon most agricultural commodity prices.

Suggested Citation

  • Giray GOZGOR & Baris KABLAMACI, 2014. "The linkage between oil and agricultural commodity prices in the light of the perceived global risk," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(7), pages 332-342.
    • Handle: RePEc:caa:jnlage:v:60:y:2014:i:7:id:183-2013-agricecon
    DOI: 10.17221/183/2013-AGRICECON
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    3. Tan Ngoc Vu & Chi Minh Ho & Thang Cong Nguyen & Duc Hong Vo, 2020. "The Determinants of Risk Transmission between Oil and Agricultural Prices: An IPVAR Approach," Agriculture, MDPI, vol. 10(4), pages 1-14, April.
    4. Xu, Ruihui & Zhang, Xuliang & Gozgor, Giray & Lau, Chi Keung Marco & Yan, Cheng, 2023. "Investor flow-chasing and price–performance puzzle: Evidence from global infrastructure funds," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Çınar, Gökhan & Uzmay, Ayse, 2017. "Does Fear (Vix Index) Incite Volatility In Food Prices?," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 5(2), April.
    6. Ebenezer, Appiah Collins & Jatoe, John Baptist D. & Mensa-Bonsu, Akwasi, 2018. "Food Price Sensitivity To Changes In Petroleum Price And Exchange Rate In Ghana: A Cointegration Analysis," 2018 Conference (2nd), August 8-11, Kumasi, Ghana 277791, Ghana Association of Agricultural Economists.
    7. Zhang, Dongna & Dai, Xingyu & Wang, Qunwei & Lau, Chi Keung Marco, 2023. "Impacts of weather conditions on the US commodity markets systemic interdependence across multi-timescales," Energy Economics, Elsevier, vol. 123(C).
    8. Giray GOZGOR & Cahit MEMIS, 2015. "Price volatility spillovers among agricultural commodity and crude oil markets: Evidence from the range-based estimator," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(5), pages 214-221.
    9. Jingye Li, 2021. "The Effect of Oil Price on China’s Grain Prices: a VAR model," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(1), pages 1-5.
    10. Rafiq, Shuddhasattwa & Bloch, Harry, 2016. "Explaining commodity prices through asymmetric oil shocks: Evidence from nonlinear models," Resources Policy, Elsevier, vol. 50(C), pages 34-48.
    11. Korhan K. Gokmenoglu & Hasan Güngör & Festus Victor Bekun, 2021. "Revisiting the linkage between oil and agricultural commodity prices: Panel evidence from an Agrarian state," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5610-5620, October.
    12. Prof. Hyacinth Ichoku & Dr. Ihuoma Anthony & Dr. Tosin Olushola & Apinran Martins, 2023. "Analyzing the Evolving Relationships among Climate Change, Insecurity, and Food Price Inflation in Nigeria: NARDL Approach," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(11), pages 100-124, November.
    13. Piotr BORAWSKI & Aneta BELDYCKA-BORAWSKA & James W. DUNN, 2018. "Price volatility of Polish agricultural commodities in the view of the Common Agricultural Policy," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(5), pages 216-226.
    14. Azeez, Rasheed Oluwaseyi, 2018. "Oil price volatility spillover effects on food prices in Nigeria," MPRA Paper 93188, University Library of Munich, Germany.
    15. Riza Radmehr & Shida Rastegari Henneberry, 2020. "Energy Price Policies and Food Prices: Empirical Evidence from Iran," Energies, MDPI, vol. 13(15), pages 1-15, August.
    16. Gozgor, Giray & Lau, Chi Keung Marco & Bilgin, Mehmet Huseyin, 2016. "Commodity markets volatility transmission: Roles of risk perceptions and uncertainty in financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 35-45.
    17. Ayhan KAPUSUZOGLU & Merve KARACAER ULUSOY, 2015. "The interactions between agricultural commodity and oil prices: an empirical analysis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(9), pages 410-421.

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    More about this item

    Keywords

    oil prices; panel data estimations; the VIX;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O24 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Trade Policy; Factor Movement; Foreign Exchange Policy

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