IDEAS home Printed from https://ideas.repec.org/a/adx/journl/v4y2022i3p170-176.html
   My bibliography  Save this article

Effects of Agricultural Commodity Prices on Agricultural Output in Nigeria

Author

Listed:
  • Anu K. Toriola

Abstract

In Nigeria, there is over-reliance on oil proceeds at the expense of revenue accrued to agriculture, which adversely affects the standard of living. The study examines the effect of commodity prices on agricultural output in Nigeria. In the empirical model, agricultural output depends on maize, wheat, soya beans, and oil prices. Data covering 1991 and 2017 from the Central Bank of Nigeria Statistical Bulletin and Food and Agricultural Organisation was analysed using a fully modified OLS (FMOLS) technique. The result shows that maize and soya bean prices positively affect agricultural output, while wheat prices and oil prices negatively affect agricultural output in Nigeria. This implies that agricultural output increases with increased agricultural commodity prices and falls with an increase in oil prices. The paper recommends the need to expand the production of agricultural commodities through a direct government partnership with farmers in the area of supply of expert knowledge, technology and credit. Also, to redirect the populace's focus from oil in favour of agriculture, there is a need to introduce a subsidy for agricultural output to make its pricing attractive and provide leverage for farmers' occasional shocks in their yield.

Suggested Citation

  • Anu K. Toriola, 2022. "Effects of Agricultural Commodity Prices on Agricultural Output in Nigeria," Journal of Economic Impact, Science Impact Publishers, vol. 4(3), pages 170-176.
    • Handle: RePEc:adx:journl:v:4:y:2022:i:3:p:170-176
    DOI: 10.52223/jei4032203
    as

    Download full text from publisher

    File URL: https://doi.org/10.52223/jei4032203
    Download Restriction: no
    File URL: https://libkey.io/10.52223/jei4032203?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. Olasunkanmi, Oseni Isiaq & Oladele, Kinbode Sakiru, 2018. "Oil price shock and agricultural commodity prices in Nigeria: A Non-Linear Autoregressive Distributed Lag (NARDL) Approach," African Journal of Economic Review, African Journal of Economic Review, vol. 6(2), July.
    5. Joakim Westerlund & Paresh Narayan, 2015. "Testing for Predictability in Conditionally Heteroskedastic Stock Returns," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 342-375.
    6. Sun, Yanpeng & Mirza, Nawazish & Qadeer, Abdul & Hsueh, Hsin-Pei, 2021. "Connectedness between oil and agricultural commodity prices during tranquil and volatile period. Is crude oil a victim indeed?," Resources Policy, Elsevier, vol. 72(C).
    7. Augusto de la Torre & Eduardo Levy Yeyati & Sergio L. Schmukler, 2003. "Living and Dying with Hard Pegs: The Rise and Fall of Argentina’s Currency Board," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 43-108, January.
    8. Dongwon Lee & Yu-chin Chen, 2014. "What Makes a Commodity Currency?," Working Papers 201420, University of California at Riverside, Department of Economics.
    9. Mehmet Balcilar & Shinhye Chang & Rangan Gupta & Vanessa Kasongo & Clement Kyei, 2014. "The Relationship between Oil and Agricultural Commodity Prices: A Quantile Causality Approach," Working Papers 201468, University of Pretoria, Department of Economics.
    10. A. P. Thirlwall, 2015. "A Model of Regional Growth Rate Differences on Kaldorian Lines," Palgrave Studies in the History of Economic Thought, in: Essays on Keynesian and Kaldorian Economics, chapter 12, pages 286-301, Palgrave Macmillan.
    11. Sun, Ting-Ting & Su, Chi-Wei & Mirza, Nawazish & Umar, Muhammad, 2021. "How does trade policy uncertainty affect agriculture commodity prices?," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    12. Mitchell, Donald, 2008. "A note on rising food prices," Policy Research Working Paper Series 4682, The World Bank.
    13. Essama-Nssah, B. & Go, Delfin S. & Kearney, Marna & Korman, Vijdan & Robinson, Sherman & Thierfelder, Karen, 2007. "Economy-wide and distributional impacts of an oil price shock on the south African economy," Policy Research Working Paper Series 4354, The World Bank.
    14. Marconi, Nelson & Reis, Cristina Fróes de Borja & Araújo, Eliane Cristina de, 2016. "Manufacturing and economic development: The actuality of Kaldor's first and second laws," Structural Change and Economic Dynamics, Elsevier, vol. 37(C), pages 75-89.
    15. Hung, Ngo Thai, 2021. "Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Resources Policy, Elsevier, vol. 73(C).
    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. Tongshuai Qiao & Liyan Han, 2023. "COVID‐19 and tail risk contagion across commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(2), pages 242-272, February.
    2. Farid, Saqib & Naeem, Muhammad Abubakr & Paltrinieri, Andrea & Nepal, Rabindra, 2022. "Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities," Energy Economics, Elsevier, vol. 109(C).
    3. Yoon, Seong-Min, 2022. "On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests," Renewable Energy, Elsevier, vol. 199(C), pages 536-545.
    4. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adewuyi, Adeolu O. & Lee, Chien-Chiang, 2022. "Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Energy Economics, Elsevier, vol. 113(C).
    5. Chen, Xiangyu & Tongurai, Jittima, 2024. "Revisiting the interdependences across global base metal futures markets: Evidence during the main waves of the COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 70(PB).
    6. Mehmet Balcilar & Festus Victor Bekun, 2020. "Spillover dynamics across price inflation and selected agricultural commodity prices," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-17, December.
    7. Ettore Gallo & Maria Cristina Barbieri Góes, 2023. "Investment, autonomous demand and long-run capacity utilization: an empirical test for the Euro Area," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 40(1), pages 225-255, April.
    8. Juncal Cunado & David Gabauer & Rangan Gupta, 2024. "Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-17, December.
    9. Dai, Zhifeng & Zhu, Junxin & Zhang, Xinhua, 2022. "Time-frequency connectedness and cross-quantile dependence between crude oil, Chinese commodity market, stock market and investor sentiment," Energy Economics, Elsevier, vol. 114(C).
    10. Germán G. Creamer & Tal Ben-Zvi, 2021. "Volatility and Risk in the Energy Market: A Trade Network Approach," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    11. Mokni, Khaled & Al-Shboul, Mohammed & Assaf, Ata, 2021. "Economic policy uncertainty and dynamic spillover among precious metals under market conditions: Does COVID-19 have any effects?," Resources Policy, Elsevier, vol. 74(C).
    12. Noureddine Benlagha & Wafa Abdelmalek, 2024. "Dynamic connectedness between energy and agricultural commodities: insights from the COVID-19 pandemic and Russia–Ukraine conflict," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 14(3), pages 781-825, September.
    13. Liu, Yunqiang & Liu, Sha & Ye, Deping & Tang, Hong & Wang, Fang, 2022. "Dynamic impact of negative public sentiment on agricultural product prices during COVID-19," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    14. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    15. Sun, Yanpeng & Mirza, Nawazish & Qadeer, Abdul & Hsueh, Hsin-Pei, 2021. "Connectedness between oil and agricultural commodity prices during tranquil and volatile period. Is crude oil a victim indeed?," Resources Policy, Elsevier, vol. 72(C).
    16. Mugera, Harriet & Gilbert, Christopher, 2015. "Structural Change in the Relationship Between Energy and Food Prices," 2015 Conference, August 9-14, 2015, Milan, Italy 212505, International Association of Agricultural Economists.
    17. Chi Zhang, 2024. "Dynamics of energy and biofuel markets in the context of rising oil prices," Agribusiness, John Wiley & Sons, Ltd., vol. 40(4), pages 866-884, October.
    18. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
    19. Doğan, Buhari & Trabelsi, Nader & Tiwari, Aviral Kumar & Ghosh, Sudeshna, 2023. "Dynamic dependence and causality between crude oil, green bonds, commodities, geopolitical risks, and policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 36-62.
    20. Cao, Yan & Cheng, Sheng, 2021. "Impact of COVID-19 outbreak on multi-scale asymmetric spillovers between food and oil prices," Resources Policy, Elsevier, vol. 74(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:adx:journl:v:4:y:2022:i:3:p:170-176. 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: Iqbal Javed (email available below). General contact details of provider: https://www.scienceimpactpub.com/journals/index.php .

    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.