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Monetary business cycle accounting for Sweden

  • Pedro Brinca EMAIL logo
Veröffentlicht/Copyright: 12. Oktober 2013

Abstract

When creating competing models of economic fluctuations, researchers typically introduce frictions in their models aiming at replicating the observed movements in the data. This paper implements a business cycle accounting procedure for the Swedish economy. Both the 1990s and the 2008 recessions are given special focus. Evidence is provided for properties that structural extensions to the business cycle model need to have in order to replicate the movements in the data. Distortions to the labor market and movements in total factor productivity are the most determinant features to be modeled with respect to real variables as well as deviations from a Taylor rule for interest rate setting, though the latter plays little role for both the 1990s and the 2008 recessions. The distortions share a structural break during the 1990s crisis but not during the recent one.


Corresponding author: Pedro Brinca, Department of Economics, Stockholm University, SE–106 91 Stockholm, Sweden, e-mail:

  1. 1

    In the prototype economy, the wedge appears as a tax to investment rather than capital holdings. Chari, Kehoe, and McGrattan (2007b) show that in theory, it makes no difference. However, it does affect the probability space for the wedges when we work with approximated economies, though the effect of including a wedge that appears as a tax to investment versus capital holdings is found by Sustek (2010) to be quantitatively irrelevant in the context of the US economy.

  2. 2

    The result is robust to different specifications of the breaking point during the crisis.

  3. 3

    In this case, the results are more sensitive to the choice of the breaking point, given that we are too close to the end of the sample and the power of the test is thus greatly decreased.

  4. 4

    The value of 1.64 is when compared with the 1990s crisis. If compared with the non-crisis periods, the result is still signficant and equal to 1.47.

  5. 5

    Bear in mind that (Chari, Kehoe, and McGrattan 2007a) define 1–τl,t as the labor wedge which leads the authors to conclude it to be procyclical.

I am grateful for comments from Martin Flodén, Annika Alexius, Johan Söderberg, John Hassler, Almut Baleer, Abdulaziz Shifa, Yangzhou Yuan, Anna Lindahl, Alper Çenesiz, Kjetil Storesletten, Pedro Raposo, Tiago Cavalcanti (the editor), anonymous referees, seminar participants at NESU, FEUC, NIPE and, in particular, Sirus Dehdari for excellent research assistance.

Appendix A

Simulated vs. Observed data for 1982–2010

Figure A1 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure A1

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

Figure A2 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure A2

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

Figure A3 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure A3

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

Appendix B

Simulated vs. Observed data for 1990–1995

Figure B1 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure B1

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

Figure B2 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure B2

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

Figure B3 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure B3

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

Appendix C

Simulated vs. Observed data for 2006–2010

Figure C1 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure C1

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

Figure C2 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure C2

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

Figure C3 Observed data “—”, Simulated data “– –”rt and πt in absolute % deviation from steady state. All others in relative % deviations.
Figure C3

Observed data “—”, Simulated data “– –

rt and πt in absolute % deviation from steady state. All others in relative % deviations.

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Published Online: 2013-10-12
Published in Print: 2013-01-01

©2013 by Walter de Gruyter Berlin Boston

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