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

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  • 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
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    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, December.
    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, December.
    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, March.
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