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Estimating DSGE Models under Partial Information

Author

Listed:
  • Paul Levine

    (University of Surrey)

  • Joseph Pearlman

    (London Metropolitan University)

  • George Perendia

    (London Metropolitan University)

Abstract

Most DSGE models and methods make inappropriate asymmetric information assumptions. They assume that all economic agents have full access to measurement of all variables and past shocks, whereas the econometricians have no access to this. An alternative assumption is that there is symmetry, in that the information set available to both agents and econometricians is incomplete. The reality lies somewhere between the two, because agents are likely to be subject to idiosyncratic shocks which they can observe, but are unable to observe other agents’ idiosyncratic shocks, as well as being unable to observe certain economy-wide shocks; however such assumptions generally lead to models that have no closed-form solution. This research aims to compare the two alternatives - the asymmetric case, as commonly used in the literature, and the symmetric case, which uses the partial information solution of Pearlman et al. (1986) using standard EU datasets. We use Bayesian MCMC methods, with log-likelihoods accounting for partial information. The work then extends the data to allow for a greater variety of measurements, and evaluates the effect on estimates, along the lines of work by Boivin and Giannoni (2005).

Suggested Citation

  • Paul Levine & Joseph Pearlman & George Perendia, 2007. "Estimating DSGE Models under Partial Information," School of Economics Discussion Papers 1607, School of Economics, University of Surrey.
  • Handle: RePEc:sur:surrec:1607
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    File URL: https://repec.som.surrey.ac.uk/2007/DP16-07.pdf
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    References listed on IDEAS

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    1. Batini, Nicoletta & Justiniano, Alejandro & Levine, Paul & Pearlman, Joseph, 2006. "Robust inflation-forecast-based rules to shield against indeterminacy," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1491-1526.
    2. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    3. 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.
    4. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    5. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
    6. Collard, Fabrice & Dellas, Harris, 2004. "The New Keynesian Model with Imperfect Information and Learning," IDEI Working Papers 273, Institut d'Économie Industrielle (IDEI), Toulouse.
    7. Lucas, Robert E, Jr, 1975. "An Equilibrium Model of the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 83(6), pages 1113-1144, December.
    8. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    9. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    10. Pearlman, Joseph & Currie, David & Levine, Paul, 1986. "Rational expectations models with partial information," Economic Modelling, Elsevier, vol. 3(2), pages 90-105, April.
    11. Joseph G. Pearlman & Thomas J. Sargent, 2005. "Knowing the Forecasts of Others," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 480-497, April.
    12. Townsend, Robert M, 1983. "Forecasting the Forecasts of Others," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 546-588, August.
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    Citations

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    Cited by:

    1. Batini, Nicoletta & Gabriel, Vasco & Levine, Paul, 2010. "A Floating versus managed exchange rate regime in a DSGE model of India," Working Papers 10/70, National Institute of Public Finance and Policy.
    2. Paul Levine & Joseph Pearlman & George Perendia & Bo Yang, 2012. "Endogenous Persistence in an estimated DSGE Model Under Imperfect Information," Economic Journal, Royal Economic Society, vol. 122(565), pages 1287-1312, December.
    3. Batini, Nicoletta & Levine, Paul & Lotti, Emanuela & Yang, Bo, 2011. "Monetary and Fiscal Policy in the Presence of Informal Labour Markets," Working Papers 11/97, National Institute of Public Finance and Policy.
    4. Nicoletta Batini & Paul Levine & Emanuela Lotti & Bo Yang, 2011. "Informality, Frictions and Monetary Policy," School of Economics Discussion Papers 0711, School of Economics, University of Surrey.
    5. Paul Levine, 2012. "Monetary policy in an uncertain world: probability models and the design of robust monetary rules," Indian Growth and Development Review, Emerald Group Publishing, vol. 5(1), pages 70-88, April.
    6. Paul Levine & Joseph Pearlman & Bo Yang, 2012. "Imperfect Information, Optimal Monetary Policy and Informational Consistency," School of Economics Discussion Papers 1012, School of Economics, University of Surrey.
    7. Cristiano Cantore & Vasco J. Gabriel & Paul Levine & Joseph Pearlman & Bo Yang, 2013. "The science and art of DSGE modelling: II – model comparisons, model validation, policy analysis and general discussion," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 19, pages 441-463 Edward Elgar Publishing.
    8. Nicoletta Batini & Paul Levine & Emanuela Lotti, 2011. "The Costs and Benefits of Informality," School of Economics Discussion Papers 0211, School of Economics, University of Surrey.
    9. Vasco J. Gabriel & Paul Levine & Joseph Pearlman & Bo Yang, 2010. "An Estimated DSGE Model of the Indian Economy," NIPE Working Papers 29/2010, NIPE - Universidade do Minho.
    10. Levine, Paul & Pearlman, Joseph, 2010. "Robust monetary rules under unstructured model uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 456-471, March.

    More about this item

    Keywords

    partial information; DSGE models; Bayesian maximum likelihood;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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