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How to construct monthly VAR proxies based on daily surprises in futures markets

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  • Kilian, Lutz

Abstract

It is common in applied work to estimate responses of macroeconomic aggregates to news shocks derived from surprise changes in daily futures prices around the date of policy announcements. This requires mapping the daily surprises into a monthly shock that may be used as an external instrument in a monthly VAR model or local projection. The standard approach has been to sum these daily surprises over the course of a given month when constructing the monthly proxy variable, ignoring the accounting relationship between daily and average monthly price data. In this paper, I discuss an alternative approach to constructing monthly proxies from daily surprises that takes account of this link and revisit the question of how to use OPEC announcements to identify news shocks in VAR models of the global oil market. The proposed approach calls into question the interpretation of the identified shock as oil supply news and implies quantitatively and qualitatively different estimates of the macroeconomic impact of OPEC announcements.

Suggested Citation

  • Kilian, Lutz, 2024. "How to construct monthly VAR proxies based on daily surprises in futures markets," Journal of Economic Dynamics and Control, Elsevier, vol. 168(C).
    • Handle: RePEc:eee:dyncon:v:168:y:2024:i:c:s0165188924001581
    DOI: 10.1016/j.jedc.2024.104966
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    1. Kilian, Lutz & Lee, Thomas K., 2014. "Quantifying the speculative component in the real price of oil: The role of global oil inventories," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 71-87.
    2. Kilian, Lutz, 2022. "Facts and fiction in oil market modeling," Energy Economics, Elsevier, vol. 110(C).
    3. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    4. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    5. Kilian, Lutz, 2022. "Understanding the estimation of oil demand and oil supply elasticities," Energy Economics, Elsevier, vol. 107(C).
    6. 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..
    7. Michael D. Bauer & Eric T. Swanson, 2023. "A Reassessment of Monetary Policy Surprises and High-Frequency Identification," NBER Macroeconomics Annual, University of Chicago Press, vol. 37(1), pages 87-155.
    8. Paula Patzelt & Ricardo Reis, 2024. "Estimating the rise in expected inflation from higher energy prices," Discussion Papers 2411, Centre for Macroeconomics (CFM).
    9. Jamie L. Cross & Bao H. Nguyen & Trung Duc Tran, 2022. "The role of precautionary and speculative demand in the global market for crude oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 882-895, August.
    10. 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.
    11. 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.
    12. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Waggoner, Daniel F., 2021. "Inference in Bayesian Proxy-SVARs," Journal of Econometrics, Elsevier, vol. 225(1), pages 88-106.
    13. Lutz Kilian & Xiaoqing Zhou, 2023. "The Econometrics of Oil Market VAR Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 65-95, Emerald Group Publishing Limited.
    14. Lutz Kilian, 2008. "The Economic Effects of Energy Price Shocks," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 871-909, December.
    15. Mikkel Plagborg-Møller & Christian K. Wolf, 2022. "Instrumental Variable Identification of Dynamic Variance Decompositions," Journal of Political Economy, University of Chicago Press, vol. 130(8), pages 2164-2202.
    16. James H. Stock & Mark W. Watson, 2018. "Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments," Economic Journal, Royal Economic Society, vol. 128(610), pages 917-948, May.
    17. Luca Gagliardone & Mark Gertler, 2023. "Oil Prices, Monetary Policy and Inflation Surges," NBER Working Papers 31263, National Bureau of Economic Research, Inc.
    18. Lutz Kilian & Clara Vega, 2011. "Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 660-671, May.
    19. Mark Gertler & Peter Karadi, 2015. "Monetary Policy Surprises, Credit Costs, and Economic Activity," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 44-76, January.
    20. Christopher R. Knittel & Robert S. Pindyck, 2016. "The Simple Economics of Commodity Price Speculation," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(2), pages 85-110, April.
    21. Marek Jarociński & Peter Karadi, 2020. "Deconstructing Monetary Policy Surprises—The Role of Information Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(2), pages 1-43, April.
    22. Inoue, Atsushi & Kilian, Lutz, 2022. "Joint Bayesian inference about impulse responses in VAR models," Journal of Econometrics, Elsevier, vol. 231(2), pages 457-476.
    23. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    24. Silvia Miranda-Agrippino & Giovanni Ricco, 2021. "The Transmission of Monetary Policy Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 74-107, July.
    25. Diego R. Känzig, 2021. "The Macroeconomic Effects of Oil Supply News: Evidence from OPEC Announcements," American Economic Review, American Economic Association, vol. 111(4), pages 1092-1125, April.
    26. Diego R. Känzig, 2023. "The Unequal Economic Consequences of Carbon Pricing," NBER Working Papers 31221, National Bureau of Economic Research, Inc.
    27. Karel Mertens & Morten O. Ravn, 2013. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States," American Economic Review, American Economic Association, vol. 103(4), pages 1212-1247, June.
    28. Mork, Knut Anton, 1989. "Oil and Macroeconomy When Prices Go Up and Down: An Extension of Hamilton's Results," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 740-744, June.
    29. Lutz Kilian & Bruce Hicks, 2013. "Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003–2008?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 385-394, August.
    30. 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.
    31. Lutz Kilian & Daniel P. Murphy, 2014. "The Role Of Inventories And Speculative Trading In The Global Market For Crude Oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 454-478, April.
    32. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    33. Dario Caldara & Edward Herbst, 2019. "Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 157-192, January.
    34. Christian K. Wolf, 2020. "SVAR (Mis)identification and the Real Effects of Monetary Policy Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(4), pages 1-32, October.
    35. Kilian, Lutz, 2019. "Measuring global real economic activity: Do recent critiques hold up to scrutiny?," Economics Letters, Elsevier, vol. 178(C), pages 106-110.
    36. Ana María Herrera & Sandeep Kumar Rangaraju, 2020. "The effect of oil supply shocks on US economic activity: What have we learned?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 141-159, March.
    37. Lutz Kilian, 2008. "Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 216-240, May.
    38. Funashima, Yoshito, 2020. "Global economic activity indexes revisited," Economics Letters, Elsevier, vol. 193(C).
    39. Bruns, Martin, 2021. "Proxy Vector Autoregressions in a Data-rich Environment," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    40. Xiaoqing Zhou, 2020. "Refining the workhorse oil market model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 130-140, January.
    41. Herwartz, Helmut & Plödt, Martin, 2016. "The macroeconomic effects of oil price shocks: Evidence from a statistical identification approach," Journal of International Money and Finance, Elsevier, vol. 61(C), pages 30-44.
    42. Demirer, RIza & Kutan, Ali M., 2010. "The behavior of crude oil spot and futures prices around OPEC and SPR announcements: An event study perspective," Energy Economics, Elsevier, vol. 32(6), pages 1467-1476, November.
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    2. Ryan Hanson & Ana María Herrera, 2025. "The Effect of Oil News Shocks on Job Creation and Destruction," Working Papers 25-06, Center for Economic Studies, U.S. Census Bureau.

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    More about this item

    Keywords

    Proxy VAR; IV; Shock aggregation; Time aggregation; Identification; OPEC; Supply news; Storage demand; Futures; Price expectations;
    All these keywords.

    JEL classification:

    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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