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Price Generating Process And Volatility In Nigerian Agricultural Commodities Market

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  • Ojogho, Osaihiomwan
  • Egware, Robert Awotu

Abstract

The literature on agricultural commodity price volatility in Nigeria has constantly reflected that an excessive price movement is harmful for both producers and consumers, particularly for those who are not able to cope with that new source of economic uncertainty. It has also raised an extensive debate on the main determinants behind the large agricultural commodity price swings observed in the last years without recourse for the price generating process. To narrow this gap, the study examined the price generating process and volatility in the Nigerian agricultural commodities market using secondary data for price series on meat, cereals, sugar, dairy and aggregate food for the period of January 1990 to February 2014. The data were analysed using the linear Gaussian State-Space (SS) model. The results of the descriptive statistics showed that the coefficients of variation for cereals (39.88%), food (32.65%) and dairy price (43.08%) were respectively higher during the overall time period (January 1990 to February 2014) than during the first (January 1990 to January 2002) and second (February 2002 to February 2014) sub-time periods. The results of the inferential statistics showed that authoregressive moving average (ARMA) model is the most selected Nigeria agricultural commodity price generating model for the time periods, that a unit increase in the past price state of cereals, dairy, sugar, meat and aggregate food would increase the future price of sugar, meat and aggregate food by N0.14, N0.28 and N0.15 respectively but decrease future price of cereals and dairy by about N1.00 and N0.21 respectively, and that the one-step ahead predicted value for the first out-of-sample period for cereals, meat, dairy and sugar price were 6317.86, 10.24 and 2.06 respectively. The Nigerian agricultural commodity prices have experienced high variability over the period, and such volatility, price-generating process and the determinants of the Nigerian food commodities prices can best be described by the simple ARMA model with time-variant hyperparameters.

Suggested Citation

  • Ojogho, Osaihiomwan & Egware, Robert Awotu, 4. "Price Generating Process And Volatility In Nigerian Agricultural Commodities Market," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(4).
  • Handle: RePEc:ags:ijfaec:229193
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    References listed on IDEAS

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    1. Anderson, Kym & Nelgen, Signe, 2012. "Trade Barrier Volatility and Agricultural Price Stabilization," World Development, Elsevier, vol. 40(1), pages 36-48.
    2. Luc Christiaensen, 2009. "Revisiting the Global Food Architecture. Lessons from the 2008 Food Crisis," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business, Review of Business and Economic Literature, vol. 0(3), pages 3345-3361.
    3. Robles, Miguel & Torero, Maximo & von Braun, Joachim, 2009. "When speculation matters:," Issue briefs 57, International Food Policy Research Institute (IFPRI).
    4. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    5. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425.
    6. Christopher Gilbert & Wyn Morgan, 2010. "Has food price volatility risen?," Department of Economics Working Papers 1002, Department of Economics, University of Trento, Italia.
    7. Hayo, Bernd & Kutan, Ali M. & Neuenkirch, Matthias, 2012. "Communication matters: US monetary policy and commodity price volatility," Economics Letters, Elsevier, vol. 117(1), pages 247-249.
    8. Yuqing Zheng & Henry Kinnucan & Henry Thompson, 2008. "News and volatility of food prices," Applied Economics, Taylor & Francis Journals, vol. 40(13), pages 1629-1635.
    9. Brian D. Wright, 2011. "The Economics of Grain Price Volatility," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 32-58.
    10. Brian D. Wright, 2011. "The Economics of Grain Price Volatility," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 32-58.
    11. Balcombe, Kelvin, 2009. "The Nature and Determinants of Volatility in Agricultural Prices," MPRA Paper 24819, University Library of Munich, Germany.
    12. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    13. Trostle, Ronald, 2008. "Factors Contributing to Recent Increases in Food Commodity Prices (PowerPoint)," Seminars 43902, USDA Economists Group.
    14. Machiko Nissanke, 2012. "Commodity Market Linkages in the Global Financial Crisis: Excess Volatility and Development Impacts," Journal of Development Studies, Taylor & Francis Journals, vol. 48(6), pages 732-750, June.
    15. Stefan Mittnik & Peter A. Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series 1203, CESifo Group Munich.
    16. Bruce A. Babcock, 2012. "The impact of US biofuel policies on agricultural price levels and volatility," China Agricultural Economic Review, Emerald Group Publishing, vol. 4(4), pages 407-426, November.
    17. Clements, Michael P & Galvão, Ana Beatriz, 2008. "Macroeconomic Forecasting With Mixed-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 546-554.
    18. Berna Karali & Gabriel J. Power, 2013. "Short- and Long-Run Determinants of Commodity Price Volatility," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(3), pages 724-738.
    19. repec:sen:rebelj:v:liv:y:2009:i:3:p:345-362 is not listed on IDEAS
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