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Does the Price of Oil Help Predict Inflation in South Africa? Historical Evidence Using a Frequency Domain Approach

Author

Listed:
  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Patrick T. Kanda

    (Department of Economics, University of Pretoria)

Abstract

The association between oil prices and inflation has remained an intriguing issue for media, academic as well as policy enquiry. Against this backdrop, we perform the frequency-domain causality test to investigate whether the growth rate of oil prices has predictive content for inflation in South Africa. As a preliminary step in our analysis, given that we use a long historical data set spanning from 1922:M01 to 2013:M07, we investigate the possibility of structural breaks in the inflation equation. We detect three breaks which define four regimes. We then perform the frequency-domain test on the full-sample, as well as, the four identified regime-specific sub-samples. We find evidence of the growth rate of oil prices to have predictive content for South African inflation based on the full-sample, as well as, two of the four regime-specific sub-samples. Given that the frequency-domain test allows us to decompose the causality across different time horizons, results also suggest that cycles of predictability of South African inflation emanating from the the growth in international oil prices could last for much longer durations for periods preceding the adoption of an inflation-targeting framework for monetary policy in South Africa.

Suggested Citation

  • Rangan Gupta & Patrick T. Kanda, 2014. "Does the Price of Oil Help Predict Inflation in South Africa? Historical Evidence Using a Frequency Domain Approach," Working Papers 201401, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201401
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    Citations

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    Cited by:

    1. Mehmet Balcilar & Reneé van Eyden & Josine Uwilingiye & Rangan Gupta, 2017. "The Impact of Oil Price on South African GDP Growth: A Bayesian Markov Switching-VAR Analysis," African Development Review, African Development Bank, vol. 29(2), pages 319-336, June.
    2. Gupta, Rangan & Kotzé, Kevin, 2017. "The role of oil prices in the forecasts of South African interest rates: A Bayesian approach," Energy Economics, Elsevier, vol. 61(C), pages 270-278.
    3. Rangan Gupta & Hylton Hollander & Mark E. Wohar, 2016. "The Impact of Oil Shocks in a Small Open Economy New-Keynesian Dynamic Stochastic General Equilibrium Model for South Africa," Working Papers 201652, University of Pretoria, Department of Economics.

    More about this item

    Keywords

    Oil prices; in flation; causality; frequency-domain;
    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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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