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Oil Price Shocks and Bond Risk Premia: Evidence from a Panel of 15 Countries

Author

Listed:
  • Iania, Leonardo

    (Université catholique de Louvain, LIDAM/LFIN, Belgium)

  • Lyrio, Marco
  • Nersisyan, Liana

    (Université catholique de Louvain, LIDAM/LFIN, Belgium)

Abstract

We study the effect of oil price shocks on bond risk premia. Based on Baumeister and Hamilton (2019), we identify the different sources of oil price shocks using a structural vector autoregressive (SVAR) model of the global market for crude oil. These structural factors are then used as unspanned factors in an affine term structure model based on the representation of Joslin et al. (2014). This is done for a total of 15 countries. Bond risk premia of net oil-exporting countries show a reaction to the structural shocks which is often statistically significant and in line with the expectation. For oil-importing developed countries, mainly the reaction to economic activity shocks is statistically significant and with the expected sign. The results for oil-importing developing countries are most of the time not statistically significant or run counter what one would expect. Among the unspanned factors, global economic activity explains most of the variability in bond risk premia. Finally, a historical decomposition around the outbreak of the COVID-19 crisis shows a variety of patterns in the evolution of bond risk premia.

Suggested Citation

  • Iania, Leonardo & Lyrio, Marco & Nersisyan, Liana, 2023. "Oil Price Shocks and Bond Risk Premia: Evidence from a Panel of 15 Countries," LIDAM Discussion Papers LFIN 2023002, Université catholique de Louvain, Louvain Finance (LFIN).
  • Handle: RePEc:ajf:louvlf:2023002
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    References listed on IDEAS

    as
    1. Kilian, Lutz, 2022. "Facts and fiction in oil market modeling," Energy Economics, Elsevier, vol. 110(C).
    2. Kandemir Kocaaslan, Ozge, 2019. "Oil price uncertainty and unemployment," Energy Economics, Elsevier, vol. 81(C), pages 577-583.
    3. Hans Dewachter & Marco Lyrio & Konstantijn Maes, 2006. "A joint model for the term structure of interest rates and the macroeconomy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 439-462, May.
    4. Korhonen, Iikka & Ledyaeva, Svetlana, 2010. "Trade linkages and macroeconomic effects of the price of oil," Energy Economics, Elsevier, vol. 32(4), pages 848-856, July.
    5. Hordahl, Peter & Tristani, Oreste & Vestin, David, 2006. "A joint econometric model of macroeconomic and term-structure dynamics," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 405-444.
    6. Cepni, Oguzhan & Gupta, Rangan & Karahan, Cenk C. & Lucey, Brian, 2022. "Oil price shocks and yield curve dynamics in emerging markets," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 613-623.
    7. Dewachter, Hans & Iania, Leonardo, 2011. "An Extended Macro-Finance Model with Financial Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(6), pages 1893-1916, December.
    8. Geert Bekaert & Seonghoon Cho & Antonio Moreno, 2010. "New Keynesian Macroeconomics and the Term Structure," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 33-62, February.
    9. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Resolving the Spanning Puzzle in Macro-Finance Term Structure Models," Review of Finance, European Finance Association, vol. 21(2), pages 511-553.
    10. Ilan Cooper, 2009. "Time-Varying Risk Premiums and the Output Gap," Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2601-2633, July.
    11. Michael D. Bauer & James D. Hamilton, 2018. "Robust Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 399-448.
    12. Christiane Baumeister & Gert Peersman & Ine Van Robays, 2010. "The Economic Consequences of Oil Shocks: Differences across Countries and Time," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    13. Park, Jungwook & Ratti, Ronald A., 2008. "Oil price shocks and stock markets in the U.S. and 13 European countries," Energy Economics, Elsevier, vol. 30(5), pages 2587-2608, September.
    14. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    15. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    16. Hamilton, James D, 1983. "Oil and the Macroeconomy since World War II," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 228-248, April.
    17. Demirer, Rıza & Ferrer, Román & Shahzad, Syed Jawad Hussain, 2020. "Oil price shocks, global financial markets and their connectedness," Energy Economics, Elsevier, vol. 88(C).
    18. Sarno, Lucio & Thornton, Daniel L. & Valente, Giorgio, 2007. "The Empirical Failure of the Expectations Hypothesis of the Term Structure of Bond Yields," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(1), pages 81-100, March.
    19. Geert Bekaert & Robert J. Hodrick, 2001. "Expectations Hypotheses Tests," Journal of Finance, American Finance Association, vol. 56(4), pages 1357-1394, August.
    20. John Y. Campbell & Robert J. Shiller, 1991. "Yield Spreads and Interest Rate Movements: A Bird's Eye View," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 495-514.
    21. Robert C Ready, 2018. "Oil Prices and the Stock Market [The vix, the variance premium and stock market volatility]," Review of Finance, European Finance Association, vol. 22(1), pages 155-176.
    22. Bekaert, Geert & Engstrom, Eric & Ermolov, Andrey, 2021. "Macro risks and the term structure of interest rates," Journal of Financial Economics, Elsevier, vol. 141(2), pages 479-504.
    23. Fama, Eugene F & Bliss, Robert R, 1987. "The Information in Long-Maturity Forward Rates," American Economic Review, American Economic Association, vol. 77(4), pages 680-692, September.
    24. 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.
    25. Lee, Chi-Chuan & Lee, Chien-Chiang & Ning, Shao-Lin, 2017. "Dynamic relationship of oil price shocks and country risks," Energy Economics, Elsevier, vol. 66(C), pages 571-581.
    26. de Jong, Frank, 2000. "Time Series and Cross-Section Information in Affine Term-Structure Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 300-314, July.
    27. Scott Joslin & Kenneth J. Singleton & Haoxiang Zhu, 2011. "A New Perspective on Gaussian Dynamic Term Structure Models," Review of Financial Studies, Society for Financial Studies, vol. 24(3), pages 926-970.
    28. Christiane Baumeister & James D. Hamilton, 2019. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," American Economic Review, American Economic Association, vol. 109(5), pages 1873-1910, May.
    29. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2016. "The economic value of predicting bond risk premia," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 247-267.
    30. Stambaugh, Robert F., 1988. "The information in forward rates : Implications for models of the term structure," Journal of Financial Economics, Elsevier, vol. 21(1), pages 41-70, May.
    31. Filippidis, Michail & Filis, George & Kizys, Renatas, 2020. "Oil price shocks and EMU sovereign yield spreads," Energy Economics, Elsevier, vol. 86(C).
    32. Umar, Zaghum & Aharon, David Y. & Esparcia, Carlos & AlWahedi, Wafa, 2022. "Spillovers between sovereign yield curve components and oil price shocks," Energy Economics, Elsevier, vol. 109(C).
    33. Refet S. Gürkaynak & Jonathan H. Wright, 2012. "Macroeconomics and the Term Structure," Journal of Economic Literature, American Economic Association, vol. 50(2), pages 331-367, June.
    34. Cologni, Alessandro & Manera, Matteo, 2008. "Oil prices, inflation and interest rates in a structural cointegrated VAR model for the G-7 countries," Energy Economics, Elsevier, vol. 30(3), pages 856-888, May.
    35. repec:cup:jfinqa:v:46:y:2011:i:06:p:1893-1916_00 is not listed on IDEAS
    36. Darrell Duffie & Rui Kan, 1996. "A Yield‐Factor Model Of Interest Rates," Mathematical Finance, Wiley Blackwell, vol. 6(4), pages 379-406, October.
    37. Ioannidis, Christos & Ka, Kook, 2018. "The impact of oil price shocks on the term structure of interest rates," Energy Economics, Elsevier, vol. 72(C), pages 601-620.
    38. Scott Joslin & Marcel Priebsch & Kenneth J. Singleton, 2014. "Risk Premiums in Dynamic Term Structure Models with Unspanned Macro Risks," Journal of Finance, American Finance Association, vol. 69(3), pages 1197-1233, June.
    39. Bikbov, Ruslan & Chernov, Mikhail, 2010. "No-arbitrage macroeconomic determinants of the yield curve," Journal of Econometrics, Elsevier, vol. 159(1), pages 166-182, November.
    40. Clements, Adam & Shield, Cody & Thiele, Stephen, 2019. "Which oil shocks really matter in equity markets?," Energy Economics, Elsevier, vol. 81(C), pages 134-141.
    41. repec:hal:journl:peer-00732517 is not listed on IDEAS
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    More about this item

    Keywords

    Oil prices shocks ; affine term structure models ; bond risk premia;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • 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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