IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v53y2019i1d10.1007_s10614-017-9717-1.html
   My bibliography  Save this article

Monetary Transmission Channels in DSGE Models: Decomposition of Impulse Response Functions Approach

Author

Listed:
  • Miroljub Labus

    (University of Belgrade)

  • Milica Labus

    (University of Belgrade)

Abstract

The paper presents decomposition of impulse response functions (IRFs) as a new diagnostic tool for dynamic stochastic general equilibrium (DSGE) models. This method works with any DSGE model of arbitrary complexity or theoretical background. It is also applicable to any policy transmission channels. We illustrate it with monetary transmission mechanisms in two New Keynesian general equilibrium models: QUEST_III model of the European Commission and Smets–Wouters model of the USA economy. For that purpose, we use DYNARE platform for solving the models and provide a MATLAB file for IRFs decomposition. The underlying software can handle decomposition of IRFs using both the first-order and the second-order approximation of Taylor series to equilibrium relations. An IRF aggregates partial contributions of all state variables to impulse responses of a model’s variable to a stochastic shock. The IRF decomposition identifies individual contributions of state variables and marks each particular channel that a policy shock uses to propagate throughout the model. We show in two illustrated cases that monetary transmission channels might be quite distinct even if DSGE models employ the same (Taylor) policy rule and reveal similar IRFs. More specifically, IRFs initiated by a monetary shock might misrepresent the pure interest rate impact on some variables. Decomposition of monetary IRFs casts more light on flexibility needed in an economy to contain negative impact of a monetary shock.

Suggested Citation

  • Miroljub Labus & Milica Labus, 2019. "Monetary Transmission Channels in DSGE Models: Decomposition of Impulse Response Functions Approach," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 27-50, January.
    • Handle: RePEc:kap:compec:v:53:y:2019:i:1:d:10.1007_s10614-017-9717-1
    DOI: 10.1007/s10614-017-9717-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-017-9717-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-017-9717-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. King, Robert G & Watson, Mark W, 2002. "System Reduction and Solution Algorithms for Singular Linear Difference Systems under Rational Expectations," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 57-86, October.
    2. Gary Anderson, 2008. "Solving Linear Rational Expectations Models: A Horse Race," Computational Economics, Springer;Society for Computational Economics, vol. 31(2), pages 95-113, March.
    3. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
    4. Ben S. Bernanke & Julio J. Rotemberg (ed.), 1997. "NBER Macroeconomics Annual 1997," MIT Press Books, The MIT Press, edition 1, volume 1, number 026252242x, April.
    5. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    6. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    7. Ratto, Marco & Roeger, Werner & Veld, Jan in 't, 2009. "QUEST III: An estimated open-economy DSGE model of the euro area with fiscal and monetary policy," Economic Modelling, Elsevier, vol. 26(1), pages 222-233, January.
    8. King, Robert G & Plosser, Charles I & Rebelo, Sergio T, 2002. "Production, Growth and Business Cycles: Technical Appendix," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 87-116, October.
    9. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
    10. Collard, Fabrice & Juillard, Michel, 2001. "Accuracy of stochastic perturbation methods: The case of asset pricing models," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 979-999, June.
    11. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
    12. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, April.
    13. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : II. New directions," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 309-341.
    14. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    15. Marimon, Ramon & Scott, Andrew (ed.), 2001. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780199248278.
    16. Ben S. Bernanke & Julio J. Rotemberg, 1997. "Editorial in "NBER Macroeconomics Annual 1997, Volume 12"," NBER Chapters, in: NBER Macroeconomics Annual 1997, Volume 12, pages 1-6, National Bureau of Economic Research, Inc.
    17. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    18. Long, John B, Jr & Plosser, Charles I, 1983. "Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 91(1), pages 39-69, February.
    19. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : I. The basic neoclassical model," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 195-232.
    20. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
    21. Ben S. Bernanke & Julio J. Rotemberg, 1997. "NBER Macroeconomics Annual 1997, Volume 12," NBER Books, National Bureau of Economic Research, Inc, number bern97-1.
    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. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    2. Schmidt, Sebastian & Wieland, Volker, 2013. "The New Keynesian Approach to Dynamic General Equilibrium Modeling: Models, Methods and Macroeconomic Policy Evaluation," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 1439-1512, Elsevier.
    3. Özer Karagedikli & Troy Matheson & Christie Smith & Shaun P. Vahey, 2010. "RBCs AND DSGEs: THE COMPUTATIONAL APPROACH TO BUSINESS CYCLE THEORY AND EVIDENCE," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 113-136, February.
    4. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    5. Alali, Walid Y., 2009. "Solution Strategies of Dynamic Stochastic General Equilibrium (DSGE) models," EconStor Preprints 269876, ZBW - Leibniz Information Centre for Economics.
    6. Alali, Walid Y., 2009. "Solution Strategies of Dynamic Stochastic General Equilibrium (DSGE) models," MPRA Paper 116480, University Library of Munich, Germany.
    7. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    8. Etro, Federico, 2017. "Research in economics and macroeconomics," Research in Economics, Elsevier, vol. 71(3), pages 373-383.
    9. Wieland, Volker & Binder, Michael & Lieberknecht, Philipp & Quintana, Jorge, 2017. "Model Uncertainty in Macroeconomics: On the Implications of Financial Frictions," CEPR Discussion Papers 12013, C.E.P.R. Discussion Papers.
    10. Wieland, Volker & Cwik, Tobias & Müller, Gernot J. & Schmidt, Sebastian & Wolters, Maik, 2012. "A new comparative approach to macroeconomic modeling and policy analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 523-541.
    11. Fujiwara Ippei, 2004. "Output Composition of the Monetary Policy Transmission Mechanism in Japan," The B.E. Journal of Macroeconomics, De Gruyter, vol. 4(1), pages 1-23, September.
    12. Bekiros Stelios & Paccagnini Alessia, 2015. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.
    13. Peter N. Ireland, 2004. "Technology Shocks in the New Keynesian Model," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 923-936, November.
    14. Alfonso Novales & Javier J. PÈrez, 2004. "Is It Worth Refining Linear Approximations to Non-Linear Rational Expectations Models?," Computational Economics, Springer;Society for Computational Economics, vol. 23(4), pages 343-377, June.
    15. Ambler, Steve & Guay, Alain & Phaneuf, Louis, 2012. "Endogenous business cycle propagation and the persistence problem: The role of labor-market frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 47-62.
    16. Lan, Hong & Meyer-Gohde, Alexander, 2014. "Solvability of perturbation solutions in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 366-388.
    17. Alfredo Villca, 2019. "Confronting DSGE model with data," Documentos de Trabajo de Valor Público 17803, Universidad EAFIT.
    18. Guangling 'Dave' Liu & Rangan Gupta & Eric Schaling, 2009. "A New-Keynesian DSGE model for forecasting the South African economy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 387-404.
    19. Lindé, Jesper & Smets, Frank & Wouters, Rafael, 2016. "Challenges for Central Banks´ Macro Models," Working Paper Series 323, Sveriges Riksbank (Central Bank of Sweden).
    20. Rupert, Peter & Šustek, Roman, 2019. "On the mechanics of New-Keynesian models," Journal of Monetary Economics, Elsevier, vol. 102(C), pages 53-69.

    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:kap:compec:v:53:y:2019:i:1:d:10.1007_s10614-017-9717-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.