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Modeling Petroleum Product Demand in Nigeria Using Structural Time Series Model (STSM) Approach

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  • Aliyu Barde Abdullahi

    (Economic Research & Data Management Department, Corporate Planning & Strategy Division of the Nigerian National Petroleum Corporation(NNPC), Corporate Headquarters, Abuja, Nigeria.)

Abstract

In this paper, the demand function for five major petroleum products consume in Nigeria namely gasoline, diesel, kerosene, fuel oil, liquefied petroleum gas (LPG) and aggregate was estimated using Structural Time Series Models (STSMs) which accounts for structural changes in energy demand estimation. STSMs incorporate stochastic rather than deterministic trend which is more general and therefore argued to be more appropriate in this study. The results suggest that the demand for petroleum products in Nigeria is both price and income inelastic and the underlying demand trends were generally stochastic in nature. LPG has relatively higher elasticities than the rest of the petroleum products, namely kerosene, gasoline, diesel and fuel oil.

Suggested Citation

  • Aliyu Barde Abdullahi, 2014. "Modeling Petroleum Product Demand in Nigeria Using Structural Time Series Model (STSM) Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 427-441.
    • Handle: RePEc:eco:journ2:2014-03-12
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    References listed on IDEAS

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    More about this item

    Keywords

    Petroleum Product; demand; STSM; Stochastic Trend;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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