IDEAS home Printed from https://ideas.repec.org/r/wly/japmet/v29y2014i3p479-496.html
   My bibliography  Save this item

Disentangling Demand And Supply Shocks In The Crude Oil Market: How To Check Sign Restrictions In Structural Vars

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Nautz, Dieter & Strohsal, Till & Netšunajev, Aleksei, 2019. "The Anchoring Of Inflation Expectations In The Short And In The Long Run," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1959-1977, July.
  2. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
  3. Jamie L. Cross & Chenghan Hou & Bao H. Nguyen, 2018. "On the China factor in international oil markets: A regime switching approach," Working Papers No 11/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  4. Li, Zheng & Zeng, Jingjing & Hensher, David A., 2023. "An efficient approach to structural breaks and the case of automobile gasoline consumption in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
  5. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
  6. Raghavan, Mala, 2020. "An analysis of the global oil market using SVARMA models," Energy Economics, Elsevier, vol. 86(C).
  7. Herwartz, Helmut & Plödt, Martin, 2014. "Sign restrictions and statistical identification under volatility breaks -- Simulation based evidence and an empirical application to monetary policy analysis," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100326, Verein für Socialpolitik / German Economic Association.
  8. Canepa, Alessandra & Zanetti Chini, Emilio & Alqaralleh, Huthaifa, 2023. "Modelling and Forecasting Energy Market Cycles: A Generalized Smooth Transition Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202318, University of Turin.
  9. Bataa, Erdenebat & Izzeldin, Marwan & Osborn, Denise R., 2016. "Changes in the global oil market," Energy Economics, Elsevier, vol. 56(C), pages 161-176.
  10. van de Ven, Dirk Jan & Fouquet, Roger, 2017. "Historical energy price shocks and their changing effects on the economy," Energy Economics, Elsevier, vol. 62(C), pages 204-216.
  11. Fabio Santeramo, 2015. "A cursory review of the identification strategies," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 3(1), pages 1-8, December.
  12. James D. Hamilton, 2021. "Measuring global economic activity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 293-303, April.
  13. Marcel Fratzscher & Malte Rieth, 2019. "Monetary Policy, Bank Bailouts and the Sovereign-Bank Risk Nexus in the Euro Area," Review of Finance, European Finance Association, vol. 23(4), pages 745-775.
  14. Kilian, Lutz, 2022. "Facts and fiction in oil market modeling," Energy Economics, Elsevier, vol. 110(C).
  15. Han, Xu, 2015. "Tests for overidentifying restrictions in Factor-Augmented VAR models," Journal of Econometrics, Elsevier, vol. 184(2), pages 394-419.
  16. Xian, Hui & Colson, Gregory & Karali, Berna & Wetzstein, Michael, 2017. "Do nonrenewable-energy prices affect renewable-energy volatility? The case of wood pellets," Journal of Forest Economics, Elsevier, vol. 28(C), pages 42-48.
  17. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
  18. Lodge, David & Manu, Ana-Simona, 2022. "EME financial conditions: Which global shocks matter?," Journal of International Money and Finance, Elsevier, vol. 120(C).
  19. Lütkepohl, Helmut & Netésunajev, Aleksei, 2014. "Structural vector autoregressions with smooth transition in variances: The interaction between US monetary policy and the stock market," SFB 649 Discussion Papers 2014-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  20. Carriero, Andrea & Marcellino, Massimiliano & Tornese, Tommaso, 2024. "Blended identification in structural VARs," Journal of Monetary Economics, Elsevier, vol. 146(C).
  21. Jadidzadeh, Ali & Serletis, Apostolos, 2017. "How does the U.S. natural gas market react to demand and supply shocks in the crude oil market?," Energy Economics, Elsevier, vol. 63(C), pages 66-74.
  22. Oliver Holtemöller & Alexander Kriwoluzky & Boreum Kwak, 2024. "Is There an Information Channel of Monetary Policy?," Discussion Papers of DIW Berlin 2084, DIW Berlin, German Institute for Economic Research.
  23. Herwartz, Helmut & Theilen, Bernd & Wang, Shu, 2024. "Unraveling the structural sources of oil production and their impact on CO2 emissions," Energy Economics, Elsevier, vol. 132(C).
  24. Lütkepohl, Helmut & Velinov, Anton, 2016. "Structural Vector Autoregressions : Checking Identifying Long-Run Restrictions via Heteroskedasticity," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 30, pages 377-392.
  25. Arampatzidis, Ioannis & Dergiades, Theologos & Kaufmann, Robert K. & Panagiotidis, Theodore, 2021. "Oil and the U.S. stock market: Implications for low carbon policies," Energy Economics, Elsevier, vol. 103(C).
  26. Yin, Libo & Zhou, Yimin, 2016. "What drives long-term oil market volatility? Fundamentals versus speculation," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-26.
  27. Dmitry Kulikov & Aleksei Netsunajev, 2016. "Identifying Shocks in Structural VAR models via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2015-8, Bank of Estonia, revised 19 Feb 2016.
  28. James D. Hamilton, 2019. "Measuring Global Economic Activity," NBER Working Papers 25778, National Bureau of Economic Research, Inc.
  29. Gong, Xu & Lin, Boqiang, 2018. "Time-varying effects of oil supply and demand shocks on China's macro-economy," Energy, Elsevier, vol. 149(C), pages 424-437.
  30. Lodge, David & Manu, Ana-Simona & Van Robays, Ine, 2023. "China’s footprint in global financial markets," Working Paper Series 2861, European Central Bank.
  31. Daniele Valenti, 2018. "Modelling the Global Price of Oil: Is there any Role for the Oil Futures-spot Spread?," Working Papers 2018.06, Fondazione Eni Enrico Mattei.
  32. Abiad, Abdul & Qureshi, Irfan A., 2023. "The macroeconomic effects of oil price uncertainty," Energy Economics, Elsevier, vol. 125(C).
  33. ElFayoumi, Khalid, 2018. "The balance sheet effects of oil market shocks: An industry level analysis," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 112-127.
  34. Bruns, Martin & Lütkepohl, Helmut, 2023. "Have the effects of shocks to oil price expectations changed?," Economics Letters, Elsevier, vol. 233(C).
  35. Nguyen, Bao H. & Okimoto, Tatsuyoshi, 2019. "Asymmetric reactions of the US natural gas market and economic activity," Energy Economics, Elsevier, vol. 80(C), pages 86-99.
  36. Gong, Xu & Chen, Liqiang & Lin, Boqiang, 2020. "Analyzing dynamic impacts of different oil shocks on oil price," Energy, Elsevier, vol. 198(C).
  37. Stella Chinye Chiemeke & Omokhagbo Mike Imafidor, 2020. "An assessment of the impact of digital technology adoption on economic growth and labour productivity in Nigeria," Netnomics, Springer, vol. 21(1), pages 103-128, December.
  38. Nguyen, Bao H. & Okimoto, Tatsuyoshi & Tran, Trung Duc, 2022. "Uncertainty-dependent and sign-dependent effects of oil market shocks," Journal of Commodity Markets, Elsevier, vol. 26(C).
  39. Michael Hachula & Malte Rieth, 2020. "Estimating the Impact of Financial Investments on Agricultural Futures Prices using Changes in Volatility," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 759-785, May.
  40. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
  41. Puonti, Päivi, 2016. "Fiscal multipliers in a structural VEC model with mixed normal errors," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 144-154.
  42. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
  43. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
  44. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.