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Have the Effects of Shocks to Oil Price Expectations Changed? Evidence from Heteroskedastic Proxy Vector Autoregressions

Author

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  • Martin Bruns

    (School of Economics, University of East Anglia)

  • Helmut Luetkepohl

    (DIW Berlin and Freie Universitaet Berlin)

Abstract

Studies of the crude oil market based on structural vector autoregressive (VAR) models typically assume a time-invariant model and transmission of shocks or they consider a time-varying model and shock transmission. We assume a heteroskedastic reduced form VAR model with time invariant slope coefficients and test for time varying impulse responses in a model for the global crude oil market that includes key macroeconomic variables. We find evidence for changes in the transmission of shocks to oil price expectations during the last decades which can be attributed to heteroskedasticity.

Suggested Citation

  • Martin Bruns & Helmut Luetkepohl, 2023. "Have the Effects of Shocks to Oil Price Expectations Changed? Evidence from Heteroskedastic Proxy Vector Autoregressions," University of East Anglia School of Economics Working Paper Series 2023-03, School of Economics, University of East Anglia, Norwich, UK..
  • Handle: RePEc:uea:ueaeco:2023-03
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    References listed on IDEAS

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    1. Olivier J. Blanchard & Marianna Riggi, 2013. "WHY ARE THE 2000s SO DIFFERENT FROM THE 1970s? A STRUCTURAL INTERPRETATION OF CHANGES IN THE MACROECONOMIC EFFECTS OF OIL PRICES," Journal of the European Economic Association, European Economic Association, vol. 11(5), pages 1032-1052, October.
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    Cited by:

    1. Lutz Kilian, 2023. "How to Construct Monthly VAR Proxies Based on Daily Futures Market Surprises," Working Papers 2310, Federal Reserve Bank of Dallas.

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    More about this item

    Keywords

    Structural vector autoregression; heteroskedastic VAR; proxy VAR; crude oil market;
    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

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