[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/ags/naaenj/280326.html
   My bibliography  Save this article

Determinants of Price of Yam in Nigeria: A Time-Series Analysis

Author

Listed:
  • Ajibade, T. B.
  • Ayinde, O. E.
  • Abdoulaye, T.
  • Ayinde, K.
Abstract
With a contribution of up to 71% to world output of yam, Nigeria remains the largest producing country with rural farmers having yam as second most commonly harvested tuber crop. Given its nutritional superiority to most roots and tubers in terms of digestible proteins and minerals and its relevance as a source of income for the poor majority of rural-farmers, the importance of yam in Nigeria cannot be overemphasized. There has however been a persistent price increase in yam, as well as other food commodities, in Nigeria. This study was therefore designed to investigate the determinants of rising yam price in Nigeria over the period 1970-2015. The study relied on time-series data sourced from FAOSTAT, Federal Bureau of Statistics and CBN Bulletin. Inferential statistics including unit-root test, cointegration and error correction model were employed in analysis. Autocorrelation was present in the model hence necessitating Cochrane-Orcutt approach. Results indicated that variables were non-stationary but became stationary after first differencing. At 5% significance level, on the long run, price of yam was determined by annual production (coef.=-0.8095), GDP (coef.=-3.009) and annual money supply (coef.=0.829). It is consequently recommended that programmes and strategies implemented to boost food production in Nigeria should be carried on viz-a-viz robust economic planning that keeps the significant macroeconomic variables at optimal levels in order to maintain the balance required for stabilization in food commodity prices. Likewise, efforts should be concerted in putting insurgency in Nigeria under checks considering the ill effect it has on farming and trading activities.

Suggested Citation

  • Ajibade, T. B. & Ayinde, O. E. & Abdoulaye, T. & Ayinde, K., 2018. "Determinants of Price of Yam in Nigeria: A Time-Series Analysis," Nigerian Journal of Agricultural Economics, Nigerian Journal of Agricultural Economics, vol. 8(1), October.
    • Handle: RePEc:ags:naaenj:280326
    DOI: 10.22004/ag.econ.280326
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/280326/files/Volume%208%281%29_Ajibade%20et%20al.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.280326?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. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    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. Das, Debojyoti & Bhatia, Vaneet & Kumar, Surya Bhushan & Basu, Sankarshan, 2022. "Do precious metals hedge crude oil volatility jumps?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    2. Bedoui, Rihab & Braiek, Sana & Guesmi, Khaled & Chevallier, Julien, 2019. "On the conditional dependence structure between oil, gold and USD exchange rates: Nested copula based GJR-GARCH model," Energy Economics, Elsevier, vol. 80(C), pages 876-889.
    3. Karakotsios, Achillefs & Katrakilidis, Constantinos & Kroupis, Nikolaos, 2021. "The dynamic linkages between food prices and oil prices. Does asymmetry matter?," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    4. Jamal Bouoiyour & Refk Selmi, 2015. "Exchange volatility and export performance in Egypt: New insights from wavelet decomposition and optimal GARCH model," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 24(2), pages 201-227, March.
    5. Sungjun Cho & Chanaka N. Ganepola & Ian Garrett, 2019. "An analysis of illiquidity in commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(8), pages 962-984, August.
    6. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Nguyen, Duc Khuong, 2020. "Dynamic volatility spillover effects between oil and agricultural products," International Review of Financial Analysis, Elsevier, vol. 69(C).
    7. de Albuquerquemello, Vinícius Phillipe & de Medeiros, Rennan Kertlly & da Nóbrega Besarria, Cássio & Maia, Sinézio Fernandes, 2018. "Forecasting crude oil price: Does exist an optimal econometric model?," Energy, Elsevier, vol. 155(C), pages 578-591.
    8. Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2021. "Forecasting energy commodity prices: A large global dataset sparse approach," Energy Economics, Elsevier, vol. 98(C).
    9. Natanelov, Valeri & McKenzie, Andrew M. & Van Huylenbroeck, Guido, 2013. "Crude oil–corn–ethanol – nexus: A contextual approach," Energy Policy, Elsevier, vol. 63(C), pages 504-513.
    10. John Baffes & Tassos Haniotis, 2016. "What Explains Agricultural Price Movements?," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(3), pages 706-721, September.
    11. Marinella Davide & Paola Vesco, 2016. "Alternative Approaches for Rating INDCs: a Comparative Analysis," Working Papers 2016.18, Fondazione Eni Enrico Mattei.
    12. Julien Chevallier & Florian Ielpo, 2013. "Volatility spillovers in commodity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 20(13), pages 1211-1227, September.
    13. Ledebur, Oliver von & Schmitz, Jochen, 2009. "Maispreisverhalten – Maispreistransmission während des Preisbooms an den Terminmärkten," Thünen Working Paper 126939, Johann Heinrich von Thünen-Institut (vTI), Federal Research Institute for Rural Areas, Forestry and Fisheries.
    14. James J Elser & Timothy J Elser & Stephen R Carpenter & William A Brock, 2014. "Regime Shift in Fertilizer Commodities Indicates More Turbulence Ahead for Food Security," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-7, May.
    15. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    16. Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan & Gkillas, Konstantinos, 2020. "Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model," Energy Economics, Elsevier, vol. 88(C).
    17. Bouoiyour, jamal & Selmi, Refk, 2014. "Exchange Rate Impact on Russia’s Exports: Some Evidence from an Evolutionary Co-spectral Analysis," MPRA Paper 59368, University Library of Munich, Germany.
    18. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    19. Maurice, Noemie & Davis, Junior, 2011. "Unravelling the underlying causes of price volatility in world coffee and cocoa commodity markets," MPRA Paper 43813, University Library of Munich, Germany, revised 2012.
    20. 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).

    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:ags:naaenj:280326. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/naaeeea.html .

    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.