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Stochastic Capital Depreciation and the Comovement of Hours and Productivity

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  • Dittmar, Robert
  • Dueker, Michael
  • Fischer, Andreas M

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 labour productivity in a neoclassical growth model. The depreciation rate is modeled as a Markov 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 non-linear decision rules in the dynamic stochastic general equilibrium model (DSGE). Our contribution to DSGE solution methodologies in the presence of Markov switching is to apply Judd's (1998) projection method to non-linear decision rules. This approach allows for non-linear 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.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 3192.

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Date of creation: Feb 2002
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Handle: RePEc:cpr:ceprdp:3192

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Keywords: hours-productivity correlation; markov switching; non-linear decision rules;

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Cited by:
  1. Paul Pichler, 2007. "On the accuracy of low-order projection methods," Economics Bulletin, AccessEcon, vol. 3(50), pages 1-8.
  2. repec:ebl:ecbull:v:3:y:2007:i:50:p:1-8 is not listed on IDEAS
  3. Francesco Furlanetto & Martin Seneca, 2011. "New perspectives on depreciation shocks as a source of business cycle fluctuations," Working Paper 2011/02, Norges Bank.
  4. repec:ebl:ecbull:v:5:y:2008:i:4:p:1-7 is not listed on IDEAS
  5. Ludmila Fadejeva & Aleksejs Melihovs, 2010. "Measuring Total Factor Productivity and Variable Factor Utilization," Eastern European Economics, M.E. Sharpe, Inc., vol. 48(5), pages 63-101, September.
  6. Poudel, Diwakar & Sandal, Leif K. & Kvamsdal, Sturla F. & Steinshamn, Stein I., 2011. "Fisheries Management under Irreversible Investment: Does Stochasticity Matter?," Discussion Papers 2011/20, Department of Business and Management Science, Norwegian School of Economics.
  7. 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.
  8. 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.
  9. Richard Harrison & George Kapetanios & Alasdair Scott & Jana Eklund, 2008. "Breaks in DSGE models," 2008 Meeting Papers 657, Society for Economic Dynamics.
  10. 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.
  11. Inwon Jang & Hyeon-seung Huh & Richard Wong, 2008. "Optimal capital investment under uncertainty: An extension," Economics Bulletin, AccessEcon, vol. 5(4), pages 1-7.
  12. 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.
  13. 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.
  14. George Bitros, 2010. "The theorem of proportionality in contemporary capital theory: An assessment of its conceptual foundations," The Review of Austrian Economics, Springer, vol. 23(4), pages 367-401, December.
  15. Jasmina Hasanhodzic & Laurence J. Kotlikoff, 2013. "Generational Risk–Is It a Big Deal?: Simulating an 80-Period OLG Model with Aggregate Shocks," BYU Macroeconomics and Computational Laboratory Working Paper Series 2013-01, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.

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