Imperatives for Modelling and Forecasting Petroleum Products Demand for Nigeria
Abstract
Modelling and forecasting petroleum products demand is a key input for energy use planning and policy formulation. This paper employs the Structural Time Series Model to estimate and forecast demand for two key petroleum products – gasoline and diesel in Nigeria. The STSM can account for structural changes in an economy through the underlying energy demand trend. STSM incorporate stochastic rather than deterministic trend which is more general and therefore argued to be more appropriate in this study. The result suggests that the demand for petroleum products in Nigeria is both price and income inelastic and fall within the range reported in the literature while the underlying demand trends were generally stochastic in nature. The demand models were forecast under three scenarios; reference case, low and high demand. The reference or base scenario describes the future based on current economic and policy environment, that is, without any specific policy shock. Under the reference case scenario, gasoline and diesel demand were forecast to reach 45.3 and 8.03 million litre per day in 2030 representing demand increase of 42% and 66% for gasoline and diesel respectively in the next fifteen years. This presents a significant challenge towards attaining self-sufficiency in meeting Nigeria’s petroleum products demands through local refining. There is therefore urgent need for the government to revamp existing refineries and encourage private investors to build new ones in order to reduce dependence on product imports.
Downloads
References
Abdullahi, A. B. (2014); Modeling Petroleum Product Demand in Nigeria Using Structural Time Series Model (STSM) Approach. International Journal of Energy Economics and Policy 4:3, pp.427-44.
Adebisi, I. (2010); Modelling UK Aggregate Energy Demand: Asymmetric Price Responses and Underlying Energy Demand Trends, M.Sc. Dissertation, University of Surrey, UK. September.
Adeyemi, O. I. and Hunt, L. C. (2007); Modelling OECD Industrial Energy Demand: Asymmetric Price Response and Energy-Saving Technical Change. Energy Economics 26:4, pp.693-709.
Africa Development Bank (2014) Nigeria Economic Outlook. http://www.afdb.org/en/countries/west-africa/nigeria/nigeria-economic-outlook/. Accessed 8 March 2014.
Amarawickrama and Hunt (2008); Electricity Demand for Sri Lanka: A Time Series Analysis Energy 33; pp.724 – 739.
Armstrong, JS, 2001 (ed); Principles of Forecasting: A handbook for researchers and
Practitioners, Norwell, MA: Kluwer Academic.
Bhattacharyya, S. C. and Timilsina, G. R. (2009); Energy Demand Models for Policy Formulation: A Comparative Study of Energy Demand Models. The World Bank Development Research Group; Environment and Energy Team. Policy Research Working Paper WPS 4866.
Bhattacharyya, S. C. and Timilsina, G. R. (2010). Modelling Energy Demand of Developing Countries: Are the Specific Features Adequately Captured? Energy Policy 38, pp.979 – 1000.
BP Statistical Review of World Energy (2014); http://www.bp.com/en/global/corporate/about-bp/energy-economics/statistical-review-of-world-energy.html. Accessed 15 February 2015.
Broadstock D. C. and Hunt, L. C. (2010); Quantifying the impact of exogenous non-economic factors on UK transport oil demand. Energy Policy 38:pp.1559 – 1565.
Craig, P. P., A. Gadgil and J. G. Koomey, (2002); What can history teach us? A retrospective examination of long-term energy forecasts for the United States. Annual Review of Energy and the Environment 27:1 pp. 83-118.
Dahl C. and Kurtubi (2001); Estimating Oil Product Demand in Indonesia Using Cointegrating Error Correction Model. Organization of Petroleum Exporting Countries (OPEC), March.
De Vita, G., Endresen, K. and Hunt, L. C. (2006); An Empirical Analysis of Energy Demand in Namibia. Energy Policy 34, pp.3447–3463.
Dimitropoulos, J., Hunt, L. C. and Judge, G. (2005); Estimating Underlying Energy Demand in UK Annual Data. Applied Economics Letters, 12 pp. 239–244.
Energy Commission of Nigeria (ECN, 2012). Energy Demand and Supply Projections for Nigeria. Director Generals Paper. http://www.energy.gov.ng/index.php?option=com_docman&task=cat_view&gid=39&Ite mid=49. Accessed 22 November 2015.
Harvey, A. C. (1989) Forecasting Structural Time Series and Kalman Filter. Cambrige University Press, Cambridge.
Hunt, L. C., Judge, G. And Ninomiya, Y. (2003a); Modelling Underlying Energy Demand Trends: A Sectoral Analysis. Energy Economics, 25:1, 93-118.
Hunt, L. C., Judge, G. And Ninomiya, Y. (2003b); Modelling Underlying Energy Demand Trends. In: Energy in a competitive market: Essays in Honour of Colin Robinson (Ed.) L. C. Hunt, Edward Elgar Publishers, Cheltenham, UK, pp.140 – 174.
Hunt, L C. And Ninomiya Y. (2003); Unravelling trends and seasonality: A structural time series analysis of transport oil demand in the UK and Japan. The Energy Journal 24: pp.63 – 96.
International Energy Agency, IEA (2011); Nigeria Energy Demand Reports. http://esds80.mcc.ac.uk/wds_iea/TableViewer/tableView.aspx. Accessed 22 march 2015.
Isa, A. H., Hamisu, S., Lamin, H. S., Ya’u, M. Z. and Olayande, J. S. (2013); The Perspective of Nigeria’s Projected Demand for Petroleum Products. Journal of Petroleum and Gas Engineering, 4:7, pp. 184 – 187.
Iwayemi, A., Adenikinju, A. And Babatunde, M. A. (2009); Estimating Petroleum Product Demand Elasticities: A Multivariate Cointegration Approach. Energy Economics, 32: pp. 73-85.
Kale, Y. (2014); Measuring Better, Rebasing/Re-benchmarking of Nigeria’s GDP. Being a Presentation of the Results of Nigeria’s GDP Rebasing/Re-benchmarking Exercise at Transcorp Hilton, Abuja, April, 6.
Koopman, S.J., Harvey, A. C., Doornik, J. A., and Shephard, N. (2009); STAMP: Structural
Time-Series Analyser, Modeller and Predictor, London, Tinberlake Consultant Press.
National Bureau of Statistics (NBS, 2012). NBS Annual Abstract of Statistics.
http://www.nigerianstat.gov.ng/nbslibrary/searchdoc. Accessed 11 April 2015.
Nigerian National Petroleum Corporation (NNPC, 2013). Annual Statistical Bulletin.
http://www.nnpcgroup.com/Portals/0/Monthly%20Performance/2013%20ASB%201st%20editi n.pdf. Accessed 20 August 2014.
Nigerian National Petroleum Corporation (NNPC, 2014). Petroleum Products Consumption in Nigeria. Annual Report.
Nwosa, P. I. and Ajibola, A. A. (2013) The Effect of Gasoline Price on Economic Sectors of Nigeria. International Journal of Energy Economics and Policy 3:1, pp.99 – 110.
Omisakin, O. A., Oyinlola, A. M. and Adeniyi, A. O. (2012); Modelling Gasoline Demand with Structural Breaks: New Evidence from Nigeria. International Journal of Energy Economics and Policy 2:1, pp.1 – 9.
Pedregal, D. J., Dejuan, O., Gomez, N. And Tobarra, M. A. (2009); Modelling Demand for Crude oil Product in Span. Energy Policy, 37: pp.4417-4427.
Sa’ad, S. and Shahbaz, M. (2012); Price and Income Elasticities of Demand for Oil Products in African Member Countries of OPEC: A Cointegration Analysis.
http://mpra.ub.uni-muenchen.de/37390/ MPRA Paper No. 37390. Accessed 16 March 2014 10
Suleiman, M. (2013); Oil Demand, Oil Prices, Economic Growth and the Resource Curse: An Empirical Analysis. Ph,D Thesis, Surrey Energy Economics Centre (SEEC), School of Economics,University of Surrey, UK.
World Bank (2015); Global Economic Prospect: Sub Saharan Africa.
http://www.worldbank.org/en/publication/global-economic-prospects/regional-outlooks/ssa.
Accessed 17 February 2015.
World Health Organization (WHO, 2014). Number of registered vehicles Data by Country. http://apps.who.int/gho/data/node.main.A995. Accessed 18 February 2015.
Wood Mackenzie (2014). Product Market Report: Nigeria. http://productmarkets.woodmac.com/Results.aspx. Accessed 20 December 2014.
TRANSFER OF COPYRIGHT
JRBEM is pleased to undertake the publication of your contribution to Journal of Research in Business Economics and Management.
The copyright to this article is transferred to JRBEM(including without limitation, the right to publish the work in whole or in part in any and all forms of media, now or hereafter known) effective if and when the article is accepted for publication thus granting JRBEM all rights for the work so that both parties may be protected from the consequences of unauthorized use.
