IDEAS home Printed from https://ideas.repec.org/p/ega/docume/200703.html
   My bibliography  Save this paper

A Back-of-the-Envelope Rule to Identify Atheoretical VARs

Author

Listed:
  • Urzúa, Carlos M.

    (Tecnológico de Monterrey, Campus Ciudad de México)

Abstract

Vector autoregressive models are often used in Macroeconomics to draw conclusions about the effects of policy innovations. However, those results depend on the researcher’s priors about the particular ordering of the variables. As an alternative, this paper presents a simple rule based on the Maximum Entropy principle that can be used to find the “most likely” ordering. The proposal is illustrated in the case of a VAR model of the U.S. economy. It is found that monetary policy shocks are better represented by innovations in the federal funds rate rather than by innovations in non-borrowed reserves.

Suggested Citation

  • Urzúa, Carlos M., 2007. "A Back-of-the-Envelope Rule to Identify Atheoretical VARs," EGAP Working Papers 2007-03, Tecnológico de Monterrey, Campus Ciudad de México.
    • Handle: RePEc:ega:docume:200703
    as

    Download full text from publisher

    File URL: http://alejandria.ccm.itesm.mx/egap/documentos/EGAP-2007-03.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    3. Christiano, Lawrence J & Eichenbaum, Martin & Evans, Charles, 1996. "The Effects of Monetary Policy Shocks: Evidence from the Flow of Funds," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 16-34, February.
    4. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 187-200, September.
    5. 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.
    6. Sims, Christopher A., 1992. "Interpreting the macroeconomic time series facts : The effects of monetary policy," European Economic Review, Elsevier, vol. 36(5), pages 975-1000, June.
    7. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    8. Marco Lippi & Lucrezia Reichlin, 1994. "Diffusion of Technical Change and the Decomposition of Output into Trend and Cycle," Review of Economic Studies, Oxford University Press, vol. 61(1), pages 19-30.
    9. Cooley, Thomas F. & Leroy, Stephen F., 1985. "Atheoretical macroeconometrics: A critique," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 283-308, November.
    10. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    11. McCallum, Bennett T., 1983. "A reconsideration of Sims' evidence concerning monetarism," Economics Letters, Elsevier, vol. 13(2-3), pages 167-171.
    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. Mustafa Caglayan & Kostas Mouratidis & Elham Saeidinezhad, 2011. "Monetary policy effects on output and exchange rates: Results from US, UK and Japan," Working Papers 2011016, The University of Sheffield, Department of Economics.
    2. Piyachart Phiromswad, 2014. "Measuring monetary policy with empirically grounded identifying restrictions," Empirical Economics, Springer, vol. 46(2), pages 681-699, March.
    3. Carlo A. Favero, 2007. "Model Evaluation in Macroeconometrics: from early empirical macroeconomic models to DSGE models," Working Papers 327, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    4. Marek Rusnak & Tomas Havranek & Roman Horvath, 2013. "How to Solve the Price Puzzle? A Meta-Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(1), pages 37-70, February.
    5. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    6. Dawid J. van Lill, 2017. "Changes in the Liquidity Effect Over Time: Evidence from Four Monetary Policy Regimes," Working Papers 704, Economic Research Southern Africa.
    7. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    8. Gouriéroux, Christian & Monfort, Alain & Renne, Jean-Paul, 2017. "Statistical inference for independent component analysis: Application to structural VAR models," Journal of Econometrics, Elsevier, vol. 196(1), pages 111-126.
    9. Marco Capasso & Alessio Moneta, 2016. "Macroeconomic responses to an independent monetary policy shock: a (more) agnostic identification procedure," LEM Papers Series 2016/36, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    10. Rafiq, M.S. & Mallick, S.K., 2008. "The effect of monetary policy on output in EMU3: A sign restriction approach," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1756-1791, December.
    11. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
    12. Soyoung Kim, 2013. "Vector autoregressive models for macroeconomic policy analysis," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 23, pages 555-572, Edward Elgar Publishing.
    13. 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.
    14. Gossé, Jean-Baptiste & Guillaumin, Cyriac, 2013. "L’apport de la représentation VAR de Christopher A. Sims à la science économique," L'Actualité Economique, Société Canadienne de Science Economique, vol. 89(4), pages 309-319, Décembre.
    15. Gert Peersman, 2005. "What caused the early millennium slowdown? Evidence based on vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 185-207.
    16. Vargas-Silva, Carlos, 2008. "Monetary policy and the US housing market: A VAR analysis imposing sign restrictions," Journal of Macroeconomics, Elsevier, vol. 30(3), pages 977-990, September.
    17. Evans, Charles L. & Marshall, David A., 1998. "Monetary policy and the term structure of nominal interest rates: Evidence and theory," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 53-111, December.
    18. Jean Louis, Rosmy & Brown, Ryan & Balli, Faruk, 2011. "On the feasibility of monetary union: Does it make sense to look for shocks symmetry across countries when none of the countries constitutes an optimum currency area?," Economic Modelling, Elsevier, vol. 28(6), pages 2701-2718.
    19. Debes, Sebastian & Gareis, Johannes & Mayer, Eric & Rüth, Sebastian, 2014. "Towards a consumer sentiment channel of monetary policy," W.E.P. - Würzburg Economic Papers 91, University of Würzburg, Department of Economics.
    20. Cochrane, John H., 1994. "Shocks," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 41(1), pages 295-364, December.

    More about this item

    Keywords

    VAR; impulse-response functions; varimin; maximum entropy; monetary policy shocks;
    All these keywords.

    JEL classification:

    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ega:docume:200703. 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: Amaranta Arroyo (email available below). General contact details of provider: https://edirc.repec.org/data/emitemx.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.