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Can the change in the composition of the US GDP explain the Great Moderation? A test via oil price shocks


  • Maravalle, Alessandro


The paper investigates whether the growing GDP share of the services sector can contribute to explain the great moderation in the US. We identify and analyze three oil price shocks and use a SVAR analysis to measure their economic impact on the US economy at both the aggregate and the sectoral level. We find mixed support for the explanation of the great moderation in terms of shrinking oil shock volatilities and observe that increases (decreases) in oil shock volatilities are contrasted by a weakening (strengthening) in their transmission mechanism. Across sectors, services are the least affected by any oil shock. As the contribution of services to the GDP volatility increases over time, we conclude that a composition effect contributed to moderate the conditional volatility to oil shocks of the US GDP.

Suggested Citation

  • Maravalle, Alessandro, 2012. "Can the change in the composition of the US GDP explain the Great Moderation? A test via oil price shocks," DFAEII Working Papers 2012-13, University of the Basque Country - Department of Foundations of Economic Analysis II.
  • Handle: RePEc:ehu:dfaeii:8766

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    Cited by:

    1. van de Ven, Dirk Jan & Fouquet, Roger, 2017. "Historical energy price shocks and their changing effects on the economy," Energy Economics, Elsevier, vol. 62(C), pages 204-216.

    More about this item


    oil price shocks; great moderation; services; structural change;

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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

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