IDEAS home Printed from https://ideas.repec.org/p/bge/wpaper/685.html
   My bibliography  Save this paper

Online Appendix to "Priors about Observables in Vector Autoregressions"

Author

Listed:
  • Marek Jarocinski
  • Albert Marcet

Abstract

Appendices A to C are in the main document. This document contains Appendices D to G.

Suggested Citation

  • Marek Jarocinski & Albert Marcet, 2013. "Online Appendix to "Priors about Observables in Vector Autoregressions"," Working Papers 685, Barcelona School of Economics.
  • Handle: RePEc:bge:wpaper:685
    as

    Download full text from publisher

    File URL: https://www.barcelonagse.eu/sites/default/files/working_paper_pdfs/685.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Weale, Martin & Wieladek, Tomasz, 2016. "What are the macroeconomic effects of asset purchases?," Journal of Monetary Economics, Elsevier, vol. 79(C), pages 81-93.

    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. Adnan Haider Bukhari & Safdar Ullah Khan, 2008. "A Small Open Economy DSGE Model for Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 963-1008.
    2. Fernando Alvarez & Francesco Lippi & Juan Passadore, 2017. "Are State- and Time-Dependent Models Really Different?," NBER Macroeconomics Annual, University of Chicago Press, vol. 31(1), pages 379-457.
    3. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    4. Anastasios Evgenidis & Stephanos Papadamou, 2021. "The impact of unconventional monetary policy in the euro area. Structural and scenario analysis from a Bayesian VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5684-5703, October.
    5. Evans, Charles L. & Marshall, David A., 2007. "Economic determinants of the nominal treasury yield curve," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 1986-2003, October.
    6. Filippo Occhino, 2001. "Monetary Policy Shocks in an Economy with Segmented Markets," Departmental Working Papers 200108, Rutgers University, Department of Economics.
    7. François R. Velde, 2009. "Chronicle of a Deflation Unforetold," Journal of Political Economy, University of Chicago Press, vol. 117(4), pages 591-634, August.
    8. Patrick A. Imam, 2015. "Shock from Graying: Is the Demographic Shift Weakening Monetary Policy Effectiveness," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 138-154, March.
    9. Vitek, Francis, 2006. "Measuring the Stance of Monetary Policy in a Small Open Economy: A Dynamic Stochastic General Equilibrium Approach," MPRA Paper 802, University Library of Munich, Germany.
    10. Stefan Laséen & Andrea Pescatori, 2020. "Financial stability and interest‐rate policy: A quantitative assessment of costs and benefit," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(3), pages 1246-1273, August.
    11. Francisco de Castro, 2006. "The macroeconomic effects of fiscal policy in Spain," Applied Economics, Taylor & Francis Journals, vol. 38(8), pages 913-924.
    12. Zsolt Darvas, 2013. "Monetary transmission in three central European economies: evidence from time-varying coefficient vector autoregressions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(2), pages 363-390, May.
    13. Carlstrom, Charles T. & Fuerst, Timothy S. & Paustian, Matthias, 2009. "Monetary policy shocks, Choleski identification, and DNK models," Journal of Monetary Economics, Elsevier, vol. 56(7), pages 1014-1021, October.
    14. Victor Echevarria Icaza & Simón Sosvilla-Rivero, 2017. "Yields on sovereign debt, fragmentation and monetary policy transmission in the euro area: A GVAR approach," Working Papers 17-01, Asociación Española de Economía y Finanzas Internacionales.
    15. Rémy Charleroy & Michael A. Stemmer, 2014. "An Emerging Market Financial Conditions Index: A VAR Approach," Documents de travail du Centre d'Economie de la Sorbonne 14068, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    16. Hyeongwoo Kim, 2018. "Fiscal Policy, Wages, and Jobs in the U.S," Auburn Economics Working Paper Series auwp2018-02, Department of Economics, Auburn University.
    17. Hyeongwoo Kim & Ying Lin, 2018. "Exchange Rate Pass-Through to Consumer Prices and the Role of Energy Prices," Auburn Economics Working Paper Series auwp2018-05, Department of Economics, Auburn University.
    18. Tianye Lin & Yangyang Ji & Sen Zhang, 2020. "Real Estate, Interest Rates, and Crowding-out Effects," CEMA Working Papers 613, China Economics and Management Academy, Central University of Finance and Economics.
    19. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    20. Croushore, Dean & Evans, Charles L., 2006. "Data revisions and the identification of monetary policy shocks," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1135-1160, September.

    More about this item

    Keywords

    vector autoregression; Bayesian estimation; prior about observables; inverse problem; monetary policy shocks;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    Statistics

    Access and download statistics

    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:bge:wpaper:685. 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: Bruno Guallar (email available below). General contact details of provider: https://edirc.repec.org/data/bargses.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.