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Revisiting the forecasting accuracy of Phillips curve: the role of oil price

Author

Listed:
  • Afees A. Salisu

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

  • Idris Ademuyiwa

    (Centre for International Governance Innovation (CIGI), Waterloo, Canada)

  • Kazeem Isah

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

Abstract

In this paper, we query whether stock prices of non-integrated firms in upstream and downstream sectors of global oil supply chain respond similarly to changes in oil prices. This enquiry relates to “homogenous expectation†assumption among investors and fund managers pertaining to returns and variances of assets of specialized firms operating in upstream and downstream sectors of the supply chain. Using theoretical framework underpinned by the arbitrage pricing theory in conjunction with heterogeneous panel ARDL regression models, we find that stock prices of upstream and downstream firms move in contrasting directions in response to changes in benchmark crude oil prices in the long-run. Specifically, we show that stock prices of upstream sector firms increased in response to increase in oil prices, while the reverse holds for stock prices of downstream firms. In the short run, returns on stock of firms in both sectors increase following increase in oil prices; but downstream firms stock returns decreased in response to negative oil price shocks. Findings further show that both sectors respond differently to episodic changes in market conditions which emanated from the global financial crisis. However, upstream firms show stronger response to changing market conditions than their downstream counterparts.

Suggested Citation

  • Afees A. Salisu & Idris Ademuyiwa & Kazeem Isah, 2017. "Revisiting the forecasting accuracy of Phillips curve: the role of oil price," Working Papers 022, Centre for Econometric and Allied Research, University of Ibadan.
  • Handle: RePEc:cui:wpaper:0022
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    More about this item

    Keywords

    OECD countries; Phillips Curve; Oil price; Inflation forecasts; Forecast evaluation;
    All these keywords.

    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
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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