This paper illustrates the main benefits of accounting for the oil futures-spot spread in a Structural Vector Autoregressive model of the international market for crude oil. To this end, we replace the proxy for global above-ground crude oil inventories with the spread, which is derived by Brent crude futures prices with maturity 3-months. This model can be motivated on the basis of several economic considerations. First, the spread exploits the price discovery role in the crude oil futures markets. Second, the spread-based model alongside a proper set of identifying assumptions accounts for the presence of informational frictions and it allows for the feedback effect from futures to spot markets. Finally, the inventory proxy is affected by measurement error. The dynamic response functions show a positive relationship between the spread and the real price of oil, triggered by speculative shocks to financial markets. Moreover, this study provides a clear picture of the historical dynamic of the real price of oil and the spread during some of the exogenous events in the oil markets.
AcharyaV.V.LochstoerL.A.RamadoraiT. (2013). “Limits to Arbitrage and Hedging: Evidence from Commodity Markets.” Journal of Financial Economics109: 441–465. https://doi.org/10.1016/j.jfineco.2013.03.003.
2.
AlquistR.BauerG.de los RiosA.D. (2014). “What Does the Convenience Yield Curve Tell Us about the Crude Oil Market?” Staff Working Papers 14-42 Bank of Canada.
3.
AlquistR.BhattaraiS.CoibionO. (2020). “Commodity-price comovement and global economic activity.” Journal of Monetary Economics112: 41–56. https://doi.org/10.1016/j.jmoneco.2019.02.004.
4.
AlquistR.KilianL. (2010). “What do we learn from the price of crude oil futures?” Journal of Applied Econometrics25: 539–573. https://doi.org/10.1002/jae.1159.
5.
Antolm-DiazJ.Rubio-RamirezJ.F. (2018). “Narrative sign restrictions for SVARs.” American Economic Review108: 2802–29. https://doi.org/10.1257/aer.20161852.
6.
BanerjeeS.KremerI. (2010). “Disagreement and learning: Dynamic patterns of trade.” The Journal of Finance65: 1269–1302. https://doi.org/10.1111/j.1540-6261.2010.01570.x.
7.
BataaE.ParkC. (2017). “Is the recent low oil price attributable to the shale revolution?” Energy Economics67: 72–82 ISSN 0140-9883. https://doi.org/10.1016/j.eneco.2017.08.011.
8.
BaumeisterC.HamiltonJ.D. (2019). “Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks.” American Economic Review109: 1873–1910. https://doi.org/10.1257/aer.20151569.
9.
BaumeisterC.KilianL. (2016). “Understanding the decline in the price of oil since June 2014.” Journal of the Association of Environmental and Resource Economists3: 131–158. https://doi.org/10.1086/684160.
10.
BaumeisterC.KorobilisD.LeeT.K. (2020). “Energy Markets and Global Economic Conditions.” Review of Economics and Statistics, pages 1-45 https://doi.org/10.3386/w27001.
11.
BaumeisterC.PeersmanG. (2013). “The role of time varying price elasticities in accounting for volatility changes in the crude oil market.” Journal of Applied Econometrics28: 1087–1109. https://doi.org/10.1002/jae.2283.
12.
BekirosS.D.DiksC.G. (2008). “The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality.” Energy Economics30: 2673–2685. https://doi.org/10.1016/j.eneco.2008.03.006.
13.
BjornlandH.C.NordvikF.M.RohrerM. (2019). “Supply flexibility in the shale patch: Evidence from North Dakota.” CAMA Working Papers 2019-56 Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University. https://doi.org/10.2139/ssrn.3434198.
14.
BornsteinG.KrusellP.RebeloS. (2018). “Lags, costs, and shocks: An equilibrium model of the oil industry.” Technical report National Bureau of Economic Research. https://doi.org/10.3386/w23423.
15.
CaoH.H.Ou-YangH. (2008). “Differences of opinion of public information and speculative trading in stocks and options.” The Review of Financial Studies22: 299–335. https://doi.org/10.1093/rfs/hhn020.
16.
CarrieroA.MumtazH.TheodoridisK.TheophilopoulouA. (2015). “The impact of uncertainty shocks under measurement error: A proxy SVAR approach.” Journal of Money, Credit and Banking47: 1223–1238. https://doi.org/10.1111/jmcb.12243.
17.
ChengI.-H.KirilenkoA.XiongW. (2015). “Convective risk flows in commodity futures markets.” Review of Finance19: 1733–1781. https://doi.org/10.1093/rof/rfu043.
18.
ChengI.-H.XiongW. (2014). “Financialization of Commodity Markets.” Annual Review of Financial Economics6: 419–441. https://doi.org/10.1146/annurev-financial-110613-034432.
19.
DvirE.RogoffK.S. (2009). “Three epochs of oil.” Technical report National Bureau of Economic Research. Ederington, L.H., C.S. Fernando, K.V. Holland, T.K. Lee, and S.C. Linn (2020). “Dynamics of Arbitrage.” Journal of Financial and Quantitative Analysis 1-57. https://doi.org/10.3386/w14927.
20.
ErbC.CampbellH.B. (2006). “The strategic and tactical value of commodity futures.” Financial Analysts Journal62: 69–97. https://doi.org/10.2469/faj.v62.n2.4084.
21.
EtulaE. (2013). “Broker-Dealer Risk Appetite and Commodity Returns.” Journal of Financial Econometrics11: 486–521.
22.
FamaE.F.K. (1987). “Commodity futures prices: some evidence on forecast power, premiums, and the theory of storage.” Journal of Business60: 55–73. https://doi.org/10.1093/jjfinec/nbs024.
23.
FantazziniD. (2016). “The oil price crash in 2014/15: Was there a (negative) financial bubble?” Energy Policy96: 383–396https://doi.org/10.1016/j.enpol.2016.06.020.
24.
Figuerola-FerrettiI.GonzaloJ. (2010). “Modelling and measuring price discovery in commodity markets.” Journal of Econometrics158: 95–107. https://doi.org/10.1016/j.jeconom.2010.03.013.
25.
Figuerola-FerrettiI.McCrorieJ.R.ParaskevopoulosI. (2019). “Mild explosivity in recent crude oil prices.” Energy Economics10438. https://doi.org/10.10167j.eneco.2019.05.002.
26.
FrankelJ.A. (2014). “Effects of speculation and interest rates in a ‘carry trade’ model of commodity prices.” Journal of International Money and Finance42: 88–112. https://doi.org/10.1016/j.jimonfin.2013.08.006.
27.
FtitiZ.JawadiF. (2019). “On the Oil Price Uncertainty.” The Energy Journal40(SI2). https://doi.org/10.5547/01956574.40.SI2.zfti.
28.
GarbadeK.D.SilberW.L. (1983). “Price movements and price discovery in futures and cash markets.” The Review of Economics and Statistics289–297. https://doi.org/10.2307/1924495.
29.
GiannoneD.ReichlinL. (2006). “Does information help recovering structural shocks from past observations?” Journal of the European Economic Association4: 455–465. https://doi.org/10.1162/jeea.2006.4.2-3.455.
30.
GortonG.B.HayashiF.RouwenhorstK.G. (2013). “The Fundamentals of Commodity Futures Returns.” Review of Finance17: 35–105. https://doi.org/10.1093/rof/rfs019.
31.
GospodinovN.NgS. (2013). “Commodity prices, convenience yields, and inflation.” Review of Economics and Statistics95: 206–219. https://doi.org/10.1162/REST_a_00242.
32.
GronwaldM. (2016). “Explosive oil prices.” Energy Economics60: 1–5. ISSN 0140-9883.
33.
HamiltonJ.D. (2019). “Measuring global economic activity.” Journal of Applied Econometrics. https://doi.org/10.1016/j.eneco.2016.09.012.
34.
HamiltonJ.D.HerreraA.M. (2004). “Comment: oil shocks and aggregate macroeconomic behavior: the role of monetary policy.” Journal of Money, credit and Banking 265–286. https://doi.org/10.1353/mcb.2004.0012.
35.
HamiltonJ.D.WuJ.C. (2014). “Risk premia in crude oil futures prices.” Journal of International Money and Finance42: 9–37. https://doi.org/10.1016/jjimonfin.2013.08.003.
36.
HerreraA.M.RangarajuS.K. (2020). “The effect of oil supply shocks on US economic activity: What have we learned?” Journal of Applied Econometrics35: 141–159. https://doi.org/10.1002/jae.2735.
37.
HotellingH. (1931). “The economics of exhaustible resources.” Journal of political Economy39: 137–175.
38.
JuvenalL.PetrellaI. (2015). “Speculation in the oil market.” Journal of Applied Econometrics30: 621–649.
39.
KaldorN. (1939). “Speculation and economic stability.” Review of Economic Studies7: 1–27.
40.
KilianL. (2009). “Not all oil price shocks are alike: disentangling demand and supply shocks in the crude oil market.” American Economic Review99: 1053–1069. https://doi.org/10.1257/aer.99.3.1053.
41.
KilianL. (2019a). “Facts and Fiction in Oil Market Modeling.” https://doi.org/10.24149/wp1907.
42.
KilianL. (2019b). “Measuring global real economic activity: Do recent critiques hold up to scrutiny?” Economics Letters178: 106–110. https://doi.org/10.1016/j.econlet.2019.03.001.
43.
KilianL.LeeT.K. (2014). “Quantifying the speculative component in the real price of oil: the role of global oil inventories.” Journal of International Money and Finance42: 71–87. https://doi.org/10.1016/j.jimonfin.2013.08.005.
KilianL.MurphyD.P. (2012). “Why agnostic sign restrictions are not enough: understanding the dynamics of oil market VAR models.” Journal of the European Economic Association10: 1166–1188. https://doi.org/10.1111Zj.1542-4774.2012.01080.x.
46.
KilianL.MurphyD.P. (2014). “The role of inventories and speculative trading in the global market for crude oil.” Journal of Applied Econometrics29: 454–478. ISSN 1099-1255. https://doi.org/10.1002/jae.2322.
KruseR.WegenerC. (2020). “ prices and its determinant.” Energy Economics85: 104328. ISSN 0140-9883. https://doi.org/10.1016/j.eneco.2019.02.020.
49.
LeeC.-C.ZengJ.-H. (2011). “Revisiting the relationship between spot and futures oil prices: evidence from quantile cointegrating regression.” Energy economics33: 924–935. https://doi.org/10.1016/j.eneco.2011.02.012.
50.
LeebH.PotscherB.M., (2006). “Can one estimate the conditional distribution of post-model-selection estimators?” The Annals of Statistics34: 2554–2591. https://doi.org/10.1214/009053606000000821.
51.
LutkepohlH.NetsunajevA. (2014). “Disentangling demand and supply shocks in the crude oil market: how to check sign restrictions in structural VARs.” Journal of Applied Econometrics29: 479–496. https://doi.org/10.1002/jae.2330.
52.
MillerM.ZhangL. (1996). “Oil Price Hikes and Development Triggers in Peace and War.” Economic Journal106: 445–457. https://doi.org/10.2307/2235259.
53.
NewellR.G.PrestB.C. (2019). “The unconventional oil supply boom: Aggregate price response from microdata.” The Energy Journal40(3). https://doi.org/10.5547/01956574.40.3.rnew.
54.
RosaC. (2014). “The high-frequency response of energy prices to US monetary policy: Understanding the empirical evidence.” Energy Economics45: 295–303. https://doi.org/10.10167j.eneco.2014.06.011.
55.
Rubio-RamfrezJ.F.WaggonerD.F.ZhaT. (2010). “Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference.” Review of Economic Studies77: 665–696. https://doi.org/10.1111/j.1467-937X.2009.00578.x.
56.
SaportaV.TudelaM.TrottM. (2009). “What can be said about the rise and fall in oil prices?” Bank of England Quarterly Bulletin Q3.
57.
Singleton (2014). “Investor flows and the 2008 boom/bust in oil prices.” Management Science60: 300–318.
58.
SmithJ.L. (2009). “World oil: market or mayhem?” Journal of Economic Perspectives23: 145–164. https://doi.org/10.1287/mnsc.2013.1756.
59.
SockinM.XiongW. (2015). “Informational frictions and commodity markets.” The Journal of Finance70: 2063–2098. https://doi.org/10.1111/jofi.12261.
60.
TsvetanovD.CoakleyJ.KellardN. (2016). “Bubbling over! The behaviour of oil futures along the yield curve.” Journal of Empirical Finance38: 516–533. https://doi.org/10.1016/jjempfin.2015.08.009.
61.
ValentiD.ManeraM.SbuelzA. (2020). “Interpreting the oil risk premium: Do oil price shocks matter?” Energy Economics91: 104906. https://doi.org/10.1016/j.eneco.2020.104906.
62.
Van HuellenS. (2020). “Approaches to Price Formation in Financialized Commodity Markets” Journal of Economic Surveys34: 219–237. https://doi.org/10.1111/joes.12342.
63.
YatchewA.NoJ.A. (2001). “Household Gasoline Demand in Canada” Econometrica69: 1697–1709.
64.
ZhouX. (2019). “Refining the workhorse oil market model” Journal of Applied Econometrics. https://doi.org/10.1111/1468-0262.00264.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
