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Incorporating judgement with DSGE models

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Abstract

Central bank policymakers often cast judgement about macroeconomic forecasts in reduced form terms, basing this on off-model information that is not easily mapped to a structural DSGE framework. We show how to compute forecasts conditioned on policymaker judgement that are the most likely conditional forecasts from the perspective of the DSGE model, thereby maximising the influence of the model structure on the forecasts. We suggest using a simple implausibility index to track the magnitude and type of policymaker judgement. This is based on the structural shocks required to return policymaker judgement. We show how to use the methods for practical use in the policy environment and also apply the techniques to condition DSGE model forecasts on: (i) the long history of published forecasts from the Reserve Bank of New Zealand; (ii) constant interest rate forecasts; and (iii) inflation forecasts from a Bayesian VAR currently used in the policy environment at the Reserve Bank of New Zealand.

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Paper provided by Reserve Bank of New Zealand in its series Reserve Bank of New Zealand Discussion Paper Series with number DP2008/10.

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Length: 22 p.
Date of creation: Jun 2008
Date of revision:
Handle: RePEc:nzb:nzbdps:2008/10

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Keywords: DSGE models; monetary policy; conditional forecasts;

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References

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  1. Reichlin, Lucrezia, 2008. "Taking DSGE models to the policy environment by Alvarez-Lois, Harrison, Piscitelli and Scott," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2453-2459, August.
  2. Eric M. Leeper & Tao Zha, 2002. "Modest policy interventions," Working Paper 2002-19, Federal Reserve Bank of Atlanta.
  3. Sims, Christopher A., 2008. "Improving monetary policy models," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2460-2475, August.
  4. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2008. "Evaluating an estimated new Keynesian small open economy model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2690-2721, August.
  5. Kirdan Lees & Troy Matheson & Christie Smith, 2007. "Open Economy Dsge-Var Forecasting And Policy Analysis: Head To Head With The Rbnz Published Forecasts," CAMA Working Papers 2007-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  6. Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," Working Paper 2002-14, Federal Reserve Bank of Atlanta.
  7. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
  8. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
  9. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
  10. Malin Adolfson & Stefan Laseen & Jesper Lindé & Mattias Villani, 2005. "An estimated New Keynesian small open economy model," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
  11. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
  12. Stephen Murchison & Andrew Rennison, 2006. "ToTEM: The Bank of Canada's New Quarterly Projection Model," Technical Reports 97, Bank of Canada.
  13. Pedro Alvarez-Lois & Richard Harrison & Laura Piscitelli & Alasdair Scott, 2005. "Taking DSGE models to the policy environment," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
  14. Malin Adolfson & Michael K. Andersson & Jesper Lindé & Mattias Villani & Anders Vredin, 2007. "Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 111-144, December.
  15. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2005. "Are Constant Interest Rate Forecasts Modest Interventions? Evidence from an Estimated Open Economy DSGE Model of the Euro Area," Working Paper Series 180, Sveriges Riksbank (Central Bank of Sweden).
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Cited by:
  1. Andrle, Michal, 2012. "Understanding DSGE Filters in Forecasting and Policy Analysis," Dynare Working Papers 16, CEPREMAP.
  2. Sra Chuenchoksan & Don Nakornthab & Surach Tanboon, 2008. "Uncertainty in the Estimation of Potential Output and Implications for the Conduct of Monetary Policy," Working Papers 2008-04, Economic Research Department, Bank of Thailand.
  3. Jan Bruha & Tibor Hledik & Tomas Holub & Jiri Polansky & Jaromir Tonner, 2013. "Incorporating Judgments and Dealing with Data Uncertainty in Forecasting at the Czech National Bank," Research and Policy Notes 2013/02, Czech National Bank, Research Department.
  4. Marco Del Negro & Frank Schorfheide, 2012. "DSGE model-based forecasting," Staff Reports 554, Federal Reserve Bank of New York.

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