IDEAS home Printed from https://ideas.repec.org/p/bny/wpaper/0040.html
   My bibliography  Save this paper

Applying Flexible Parameter Restrictions in Markov-Switching Vector Autoregression Models

Author

Listed:
  • Andrew Binning
  • Junior Maih

Abstract

We present a new method for imposing parameter restrictions in Markov-Switching Vector Autoregression (MS-VAR) models. Our method is more flexible than competing methodologies and easily handles a range of parameter restrictions over different equations, regimes and parameter types. We also expand the range of priors used in the MS-VAR literature. We demonstrate the versatility of our approach using three appropriate examples.

Suggested Citation

  • Andrew Binning & Junior Maih, 2015. "Applying Flexible Parameter Restrictions in Markov-Switching Vector Autoregression Models," Working Papers No 12/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    • Handle: RePEc:bny:wpaper:0040
    as

    Download full text from publisher

    File URL: https://www.bi.edu/contentassets/572739a903c340ee973412a9adbadcf6/working_camp_12-2015.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    2. Daniel F. Waggoner & Hongwei Wu & Tao Zha, 2014. "The Dynamic Striated Metropolis-Hastings Sampler for High-Dimensional Models," FRB Atlanta Working Paper 2014-21, Federal Reserve Bank of Atlanta.
    3. Glenn Rudebusch & Lars E.O. Svensson, 1999. "Policy Rules for Inflation Targeting," NBER Chapters, in: Monetary Policy Rules, pages 203-262, National Bureau of Economic Research, Inc.
    4. Sims, Christopher A. & Waggoner, Daniel F. & Zha, Tao, 2008. "Methods for inference in large multiple-equation Markov-switching models," Journal of Econometrics, Elsevier, vol. 146(2), pages 255-274, October.
    5. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    6. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    7. Robert A Buckle & Kunhong Kim & Heather Kirkham & Nathan McLellan & Jared Sharma, 2002. "A structural VAR model of the New Zealand business cycle," Treasury Working Paper Series 02/26, New Zealand Treasury.
    8. Tim Robinson, 2013. "Estimating and Identifying Empirical BVAR-DSGE Models for Small Open Economies," RBA Research Discussion Papers rdp2013-06, Reserve Bank of Australia.
    9. Cushman, David O. & Zha, Tao, 1997. "Identifying monetary policy in a small open economy under flexible exchange rates," Journal of Monetary Economics, Elsevier, vol. 39(3), pages 433-448, August.
    10. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    11. Sims, Christopher A. & Zha, Tao, 2006. "Does Monetary Policy Generate Recessions?," Macroeconomic Dynamics, Cambridge University Press, vol. 10(2), pages 231-272, April.
    12. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270, CPB Netherlands Bureau for Economic Policy Analysis.
    13. Zha, Tao, 1999. "Block recursion and structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 90(2), pages 291-316, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Waggoner, Daniel F. & Zha, Tao, 2003. "Likelihood preserving normalization in multiple equation models," Journal of Econometrics, Elsevier, vol. 114(2), pages 329-347, June.
    2. Summers, Peter M., 2001. "Forecasting Australia's economic performance during the Asian crisis," International Journal of Forecasting, Elsevier, vol. 17(3), pages 499-515.
    3. Leeper, Eric M. & Zha, Tao, 2003. "Modest policy interventions," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1673-1700, November.
    4. Joris de Wind, 2014. "Time variation in the dynamic effects of unanticipated changes in tax policy," CPB Discussion Paper 271, CPB Netherlands Bureau for Economic Policy Analysis.
    5. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    6. Joris de Wind, 2014. "Time variation in the dynamic effects of unanticipated changes in tax policy," CPB Discussion Paper 271.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    7. Mauro Sayar Ferreira & André Cordeiro Valério, 2020. "Global shocks and emerging economies: disentangling the commodity roller coaster," Textos para Discussão Cedeplar-UFMG 623, Cedeplar, Universidade Federal de Minas Gerais.
    8. Waggoner, Daniel F. & Wu, Hongwei & Zha, Tao, 2016. "Striated Metropolis–Hastings sampler for high-dimensional models," Journal of Econometrics, Elsevier, vol. 192(2), pages 406-420.
    9. Marek Jarociński & Bartosz Maćkowiak, 2017. "Granger Causal Priority and Choice of Variables in Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 319-329, May.
    10. Lhuissier, Stéphane, 2017. "Financial intermediaries’ instability and euro area macroeconomic dynamics," European Economic Review, Elsevier, vol. 98(C), pages 49-72.
    11. Rokon Bhuiyan, 2012. "Monetary transmission mechanisms in a small open economy: a Bayesian structural VAR approach," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 45(3), pages 1037-1061, August.
    12. Fink, Fabian & Schüler, Yves S., 2015. "The transmission of US systemic financial stress: Evidence for emerging market economies," Journal of International Money and Finance, Elsevier, vol. 55(C), pages 6-26.
    13. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    14. Voss, G.M. & Willard, L.B., 2009. "Monetary policy and the exchange rate: Evidence from a two-country model," Journal of Macroeconomics, Elsevier, vol. 31(4), pages 708-720, December.
    15. Daniel F. Waggoner & Hongwei Wu & Tao Zha, 2014. "The Dynamic Striated Metropolis-Hastings Sampler for High-Dimensional Models," FRB Atlanta Working Paper 2014-21, Federal Reserve Bank of Atlanta.
    16. Tomas Konecny & Oxana Babecka-Kucharcukova, 2016. "Credit Spreads and the Links between the Financial and Real Sectors in a Small Open Economy: The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 302-321, August.
    17. Fabian Fink & Yves S. Schüler, 2013. "The Transmission of US Financial Stress: Evidence for Emerging Market Economies," Working Paper Series of the Department of Economics, University of Konstanz 2013-01, Department of Economics, University of Konstanz.
    18. Jennifer E. Roush, 2001. "Evidence uncovered: long-term interest rates, monetary policy, and the expectations theory," International Finance Discussion Papers 712, Board of Governors of the Federal Reserve System (U.S.).
    19. Margaux MacDonald & Michał Ksawery Popiel, 2020. "Unconventional Monetary Policy in a Small Open Economy," Open Economies Review, Springer, vol. 31(5), pages 1061-1115, November.
    20. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bny:wpaper:0040. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Helene Olsen (email available below). General contact details of provider: https://edirc.repec.org/data/cambino.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.