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Improving the Predictive ability of oil for inflation: An ADL-MIDAS Approach

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  • Afees A. Salisu

    (Centre for Econometric and Allied Research, University of Ibadan)

  • Ahamuefula Ephraim Ogbonna

    (Centre for Econometric and Allied Research, University of Ibadan)

Abstract

This paper attempts to improve the predictive ability of oil for inflation by incorporating mixed data sampling regression model into the autoregressive distributed lag model. The efficiency of the conventionally used models, which are based on same frequency of variables, is challenged on the basis of the concealed information in low frequency series. Using data covering OECD countries, we find that the ADL-MIDAS seems to outperform all the other competing models, a feat attributable to the integration of more information from a higher frequency oil price series in the forecast of a low frequency inflation series. In addition, including oil price in inflation model produces more accurate results than the model that excludes it.

Suggested Citation

  • Afees A. Salisu & Ahamuefula Ephraim Ogbonna, 2017. "Improving the Predictive ability of oil for inflation: An ADL-MIDAS Approach," Working Papers 025, Centre for Econometric and Allied Research, University of Ibadan.
    • Handle: RePEc:cui:wpaper:0025
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    References listed on IDEAS

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    1. Salisu, Afees A. & Ogbonna, Ahamuefula E., 2019. "Another look at the energy-growth nexus: New insights from MIDAS regressions," Energy, Elsevier, vol. 174(C), pages 69-84.
    2. Moses Tule & Afees A. Salisu & Charles Chimeke, 2018. "You are what you eat: The role of oil price in Nigeria inflation forecast," Working Papers 040, Centre for Econometric and Allied Research, University of Ibadan.
    3. Moses Tule & Afees Salisu & Charles Chiemeke, 2020. "Improving Nigeria’s Inflation Forecast with Oil Price: The Role of Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 191-229, March.
    4. Afees A. Salisu & Rangan Gupta, 2021. "How Do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(15), pages 4286-4311, December.

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    Keywords

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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