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Inspecting the noisy mechanism: the stochastic growth model with partial information

Author

Listed:
  • Liam Graham

    (University College)

  • Stephen Wright

    (Birkbeck College)

Abstract

We derive a framework (and provide a software toolkit) which allows the dynamic general equilibrium modeller to specify what variables are in households' information sets, and the degree to which these variables are measured with error. We apply this framework to a canonical real business cycle model and show that which variables are observable has a significant effect, both qualitatively and quantitatively, on the dynamics of the model. Specifically, we find (i) The standard decentralised equilibrium, with households only observing returns and not aggregate quantities, is not stable to arbitrarily small measurement error (ii) A stable solution does exist, but it is dramatically different from the full-information case (iii) Having aggregate output data, even if relatively noisy, brings the economy much closer to the full-information solution

Suggested Citation

  • Liam Graham & Stephen Wright, 2006. "Inspecting the noisy mechanism: the stochastic growth model with partial information," Computing in Economics and Finance 2006 207, Society for Computational Economics.
  • Handle: RePEc:sce:scecfa:207
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    References listed on IDEAS

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    3. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
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    5. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    6. Campbell, John Y., 1994. "Inspecting the mechanism: An analytical approach to the stochastic growth model," Journal of Monetary Economics, Elsevier, vol. 33(3), pages 463-506, June.
    7. Aoki, Kosuke, 2006. "Optimal commitment policy under noisy information," Journal of Economic Dynamics and Control, Elsevier, vol. 30(1), pages 81-109, January.
    8. Orphanides, Athanasios, 2003. "Monetary policy evaluation with noisy information," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 605-631, April.
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    11. Edward C. Prescott & Rajnish Mehra, 2005. "Recursive Competitive Equilibrium: The Case Of Homogeneous Households," World Scientific Book Chapters,in: Theory Of Valuation, chapter 11, pages 357-371 World Scientific Publishing Co. Pte. Ltd..
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    13. Aoki, Kosuke, 2003. "On the optimal monetary policy response to noisy indicators," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 501-523, April.
    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. Pearlman, Joseph G., 1992. "Reputational and nonreputational policies under partial information," Journal of Economic Dynamics and Control, Elsevier, vol. 16(2), pages 339-357, April.
    16. Quah, Danny, 1990. "Permanent and Transitory Movements in Labor Income: An Explanation for "Excess Smoothness" in Consumption," Journal of Political Economy, University of Chicago Press, vol. 98(3), pages 449-475, June.
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    18. Orphanides, Athanasios & Porter, Richard D. & Reifschneider, David & Tetlow, Robert & Finan, Frederico, 2000. "Errors in the measurement of the output gap and the design of monetary policy," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 117-141.
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    More about this item

    Keywords

    DGE; Partial information; Measurement error;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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