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Refining the Workhorse Oil Market Model

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  • Xiaoqing Zhou

Abstract

The Kilian and Murphy (2014) structural vector autoregressive model has become the workhorse model for the analysis of oil markets. I explore various refinements and extensions of this model, including the effects of (1) correcting an error in the measure of global real economic activity, (2) explicitly incorporating narrative sign restrictions into the estimation, (3) relaxing the upper bound on the impact price elasticity of oil supply, (4) evaluating the implied posterior distribution of the structural models, and (5) extending the sample. I demonstrate that the substantive conclusions of Kilian and Murphy (2014) are largely unaffected by these changes.

Suggested Citation

  • Xiaoqing Zhou, 2019. "Refining the Workhorse Oil Market Model," Working Papers 1910, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddwp:1910
    DOI: 10.24149/wp1910
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    File URL: https://www.dallasfed.org/-/media/documents/research/papers/2019/wp1910.pdf
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    References listed on IDEAS

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    1. Juan Antolín-Díaz & Juan F. Rubio-Ramírez, 2018. "Narrative Sign Restrictions for SVARs," American Economic Review, American Economic Association, vol. 108(10), pages 2802-2829, October.
    2. Bassam Fattouh, Lutz Kilian, and Lavan Mahadeva, 2013. "The Role of Speculation in Oil Markets: What Have We Learned So Far?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    3. Richard G. Newell and Brian C. Prest, 2019. "The Unconventional Oil Supply Boom: Aggregate Price Response from Microdata," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    4. Kilian, Lutz & Zhou, Xiaoqing, 2018. "Modeling fluctuations in the global demand for commodities," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 54-78.
    5. Juan Antolin-Diaz & Juan F. Rubio-Ramirez, 2016. "Narrative Sign Restrictions for SVARs," FRB Atlanta Working Paper 2016-16, Federal Reserve Bank of Atlanta.
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    Citations

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    Cited by:

    1. Kilian, Lutz, 2019. "Facts and Fiction in Oil Market Modeling," CEPR Discussion Papers 14047, C.E.P.R. Discussion Papers.
    2. Atsushi Inoue & Lutz Kilian, 2020. "The Role of the Prior in Estimating VAR Models with Sign Restrictions," Working Papers 2030, Federal Reserve Bank of Dallas.
    3. Kilian, Lutz, 2019. "Measuring global real economic activity: Do recent critiques hold up to scrutiny?," Economics Letters, Elsevier, vol. 178(C), pages 106-110.
    4. Lutz Kilian & Xiaoqing Zhou, 2020. "The Econometrics of Oil Market VAR Models," CESifo Working Paper Series 8153, CESifo.
    5. Kilian, Lutz & Zhou, Xiaoqing, 2019. "Oil Prices, Exchange Rates and Interest Rates," CEPR Discussion Papers 13478, C.E.P.R. Discussion Papers.
    6. Kilian, Lutz & Zhou, Xiaoqing, 2020. "Does drawing down the U.S. strategic petroleum reserve help stabilize oil prices?," CFS Working Paper Series 647, Center for Financial Studies (CFS).
    7. Lutz Kilian & Xiaoqing Zhou, 2020. "Does drawing down the US Strategic Petroleum Reserve help stabilize oil prices?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 673-691, September.
    8. Zeina Alsalman, 0. "Does the source of oil supply shock matter in explaining the behavior of U.S. consumer spending and sentiment?," Empirical Economics, Springer, vol. 0, pages 1-28.
    9. Rausser, Gordon & Stuermer, Martin, 2020. "A Dynamic Analysis of Collusive Action: The Case of the World Copper Market, 1882-2016," MPRA Paper 104708, University Library of Munich, Germany.

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    More about this item

    Keywords

    Oil market; global real activity; structural VAR; narrative sign restrictions; identification; Bayesian inference;

    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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