Disentangling demand and supply shocks in the crude oil market: How to check sign restrictions in structural vars

Journal of Applied Econometrics

Volumn 29, Issue 3, 2014, Pages 479-496

  Lütkepohl, Helmut ^a   Netšunajev, Aleksei ^b  

^a FREIE UNIVERSITÄT BERLIN   (Germany)

^b EUROPEAN UNIVERSITY INSTITUTE   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84878220535     PISSN: 08837252     EISSN: 10991255     Source Type: Journal    
DOI: 10.1002/jae.2330     Document Type: Article

References (35)

1. Barsky RB, Kilian L. 2004. Oil and the macroeconomy since the 1970s. Journal of Economic Perspectives 18: 115-134.
2. Baumeister C, Peersman G. 2012. The role of time-varying price elasticities in accounting for volatility changes in the crude oil market. Journal of Applied Econometrics. DOI: 10.1002/jae.2283.
3. Benati L, Mumtaz H. 2007. U.S. evolving macroeconomic dynamics: a structural investigation. Working Paper 746, European Central Bank, Frankfurt.
4. Bouakez H, Normandin M. 2010. Fluctuations in the foreign exchange market: how important are monetary policy shocks? Journal of International Economics 81: 139-153.
5. Candelon B, Lütkepohl H. 2001. On the reliability of Chow-type tests for parameter constancy in multivariate dynamic models. Economics Letters 73: 155-160.
6. Canova F, De Nicoló G. 2002. Monetary disturbances matter for business fluctuations in the G-7. Journal of Monetary Economics 49: 1131-1159.
7. Cogley T, Sargent TJ. 2005. Drifts and volatilities: monetary policies and outcomes in the post WWII US. Review of Economic Dynamics 8: 262-302.
8. Doucet A, Godsill SJ, Robert CP. 2002. Marginal maximum a posteriori estimation using Markov chain Monte Carlo. Statistics and Computing 12: 77-84.
9. Faust J 1998. The robustness of identified VAR conclusions about money. Carnegie- Rochester Conference Series in Public Policy 49: 207-244.
10. Fry R, Pagan A. 2011. Sign restrictions in structural vector autoregressions: a critical review. Journal of Economic Literature 49: 938-960.
11. Hamilton JD. 2011. Nonlinearities and the macroeconomic effects of oil prices. Macroeconomic Dynamics 15: 364-378.
12. Herwartz H, Lütkepohl H. 2011. Structural vector autoregressions with Markov switching: combining conventional with statistical identification of shocks. Working paper series, EUI, Florence.
13. Jacquier E, Johannes M, Polson N. 2007. MCMC maximum likelihood for latent state models. Journal of Econometrics 137: 615-640.
14. Kilian L 2009. Not all oil price shocks are alike: disentangling demand and supply shocks in the crude oil market. American Economic Review 99: 1053-1069.
15. Kilian L, Murphy D. 2012. Why agnostic sign restrictions are not enough: understanding the dynamics of oil market VAR models. Journal of the European Economic Association 10: 1166-1188.
16. Kilian L, Park C. 2009. The impact of oil price shocks on the U.S. stock market. International Economic Review 50: 1267-1287.
17. Kilian L, Vigfusson RJ. 2011. Nonlinearities in the oil price-output relationship. Macroeconomic Dynamics 15: 337-363.
18. Koop G, Korobolis D. 2009. Bayesian multivariate time series methods for empirical macroeconomics. Foundations and Trends in Econometrics 3: 267-358.
19. Krolzig H-M 1997. Markov-Switching Vector Autoregressions: Modelling, Statistical Inference, and Application to Business Cycle Analysis. Springer: Berlin.
20. Lanne M, Lütkepohl H. 2008. Identifying monetary policy shocks via changes in volatility. Journal of Money, Credit, and Banking 40: 1131-1149.
21. Lanne M, Lütkepohl H, Maciejowska K. 2010. Structural vector autoregressions with Markov switching. Journal of Economic Dynamics and Control 34: 121-131.
22. Lippi F, Nobili A. 2012. Oil and the macroeconomy: a quantitative structural analysis. Journal of the European Economic Association 10: 1059-1083.
23. Lütkepohl H 2005. New Introduction to Multiple Time Series Analysis. Springer: Berlin.
24. Moon HR, Schorfheide F. 2009. Bayesian and frequentist inference in partially identified models. Working Paper 14882, NBER, Cambridge, MA.
25. Moon HR, Schorfheide F, Granziera E, Lee M. 2009. Inference for VARs identified with sign restrictions. Working paper, USC, Los Angeles, CA.
26. Normandin M, Phaneuf L. 2004. Monetary policy shocks: testing identification conditions under time-varying conditional volatility. Journal of Monetary Economics 51: 1217-1243.
27. Peersman G, Van Robays I. 2009. Oil and the Euro area economy. Economic Policy 24: 605-651.
28. Peersman G, Van Robays I. 2012. Cross-country differences in the effects of oil shocks. Energy Economics 34: 1532-1547.
29. Primiceri GE. 2005. Time varying structural vector autoregressions and monetary policy. Review of Economic Studies 72: 821-852.
30. Rigobon R 2003. Identification through heteroskedasticity. The Review of Economics and Statistics 85: 777-792.
31. Rigobon R, Sack B. 2003. Measuring the reaction of monetary policy to the stock market. Quarterly Journal of Economics 118: 639-669.
32. Rubio-Ramirez JF, Waggoner D, Zha T. 2005. Markov-switching structural vector autoregressions: theory and applications. Discussion paper, Federal Reserve Bank of Atlanta.
33. Sims CA, Zha T. 2006. Were there regime switches in U.S. monetary policy? American Economic Review 96: 54-81.
34. Sims CA, Waggoner DF, Zha T. 2008. Methods for inference in large multiple-equation Markov-switching models. Journal of Econometrics 146: 255-274.
35. Uhlig H. 2005. What are the effects of monetary policy on output? Results from an agnostic identification procedure. Journal of Monetary Economics 52: 381-419.