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Stochastic Capital Depreciation and the Comovement of Hours and Productivity

Author

Listed:
  • Fischer, Andreas

    (Swiss National Bank and CEPR)

  • Michael J Dueker
  • Robert D Dittmar

Abstract

In this article, we demonstrate that a small degree of stochastic variation in the depreciation rate of capital can greatly reduce the comovement between hours worked and labor productivity in a neoclassical growth model. The depreciation rate is modeled as a Markov process, as opposed to a linear autoregressive process, to place a strict upper bound and to ensure that variation and not the level of the rate is driving the result. Markov switching implies nonlinear decision rules in the dynamic stochastic general equilibrium model (DSGE). Our contribution to solving DSGE models with Markov switching is to apply Judd's (1998) projection method to capture the nonlinearity in the decision rules. This approach allows for nonlinear decision rules in a richer set of models with many more state variables than can be solved with grid-based approximations. The results presented here suggest that Markov switching parameters offer a powerful extension to DSGE models.

Suggested Citation

  • Fischer, Andreas & Michael J Dueker & Robert D Dittmar, 2003. "Stochastic Capital Depreciation and the Comovement of Hours and Productivity," Royal Economic Society Annual Conference 2003 80, Royal Economic Society.
    • Handle: RePEc:ecj:ac2003:80
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    1. is not listed on IDEAS
    2. Furlanetto, Francesco & Seneca, Martin, 2014. "New Perspectives On Depreciation Shocks As A Source Of Business Cycle Fluctuations," Macroeconomic Dynamics, Cambridge University Press, vol. 18(6), pages 1209-1233, September.
    3. repec:ebl:ecbull:v:3:y:2007:i:50:p:1-8 is not listed on IDEAS
    4. Inwon Jang & Hyeon-seung Huh & Richard Wong, 2008. "Optimal capital investment under uncertainty: An extension," Economics Bulletin, AccessEcon, vol. 5(4), pages 1-7.
    5. Richard Harrison & George Kapetanios & Alasdair Scott & Jana Eklund, 2008. "Breaks in DSGE models," 2008 Meeting Papers 657, Society for Economic Dynamics.
    6. Anatoliy Belaygorod & Michael J. Dueker, 2007. "The price puzzle and indeterminacy in an estimated DSGE model," Working Papers 2006-025, Federal Reserve Bank of St. Louis.
    7. George Bitros, 2010. "The theorem of proportionality in contemporary capital theory: An assessment of its conceptual foundations," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 23(4), pages 367-401, December.
    8. Eric Kemp-Benedict & Jonathan Lamontagne & Timothy Laing & Crystal Drakes, 2019. "Climate Impacts on Capital Accumulation in the Small Island State of Barbados," Sustainability, MDPI, vol. 11(11), pages 1-23, June.
    9. Paul Pichler, 2007. "On the accuracy of low-order projection methods," Economics Bulletin, AccessEcon, vol. 3(50), pages 1-8.
    10. Bitros, George C., 2009. "The Theorem of Proportionality in Mainstream Capital Theory: An Assessment of its Conceptual Foundations," MPRA Paper 17436, University Library of Munich, Germany.
    11. Ludmila Fadejeva & Aleksejs Melihovs, 2010. "Measuring Total Factor Productivity and Variable Factor Utilization," Eastern European Economics, Taylor & Francis Journals, vol. 48(5), pages 63-101, September.
    12. Tom Holden, 2012. "Medium-frequency cycles and the remarkable near trend-stationarity of output," School of Economics Discussion Papers 1412, School of Economics, University of Surrey.
    13. Deli, Yota D., 2016. "Endogenous capital depreciation and technology shocks," Journal of International Money and Finance, Elsevier, vol. 69(C), pages 318-338.
    14. repec:ebl:ecbull:v:5:y:2008:i:4:p:1-7 is not listed on IDEAS
    15. Karamé, Frédéric, 2018. "A new particle filtering approach to estimate stochastic volatility models with Markov-switching," Econometrics and Statistics, Elsevier, vol. 8(C), pages 204-230.
    16. Jasmina Hasanhodzic & Laurence J. Kotlikoff, 2013. "Generational Risk - Is It a Big Deal?: Simulating an 80-Period OLG Model with Aggregate Shocks," NBER Working Papers 19179, National Bureau of Economic Research, Inc.
    17. F. Canova & F. Ferroni & C. Matthes, 2015. "Approximating time varying structural models with time invariant structures," Working papers 578, Banque de France.
    18. Pedro P. Alvarez-Lois, 2005. "Production Inflexibilities and the Cost Channel of Monetary Policy," Economic Inquiry, Western Economic Association International, vol. 43(1), pages 170-193, January.
    19. Poudel, Diwakar & Sandal, Leif K. & Kvamsdal, Sturla F. & Steinshamn, Stein I., 2011. "Fisheries Management under Irreversible Investment: Does Stochasticity Matter?," Discussion Papers 2011/20, Norwegian School of Economics, Department of Business and Management Science.
    20. Belaygorod, Anatoliy & Dueker, Michael, 2009. "Indeterminacy, change points and the price puzzle in an estimated DSGE model," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 624-648, March.

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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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