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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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  • Jaromír Beneš & Andrew Binning & Kirdan Lees, 2008. "Incorporating judgement with DSGE models," Reserve Bank of New Zealand Discussion Paper Series DP2008/10, Reserve Bank of New Zealand.
  • Handle: RePEc:nzb:nzbdps:2008/10
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    1. Kirdan Lees & Troy Matheson & Christie Smith, 2007. "Open economy DSGE-VAR forecasting and policy analysis - head to head with the RBNZ published forecasts," Reserve Bank of New Zealand Discussion Paper Series DP2007/01, Reserve Bank of New Zealand.
    2. Leeper, Eric M. & Zha, Tao, 2003. "Modest policy interventions," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1673-1700, November.
    3. 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.
    4. 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.
    5. 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.
    6. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    7. 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.
    8. 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.).
    9. 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.
    10. Stephen Murchison & Andrew Rennison, 2006. "ToTEM: The Bank of Canada's New Quarterly Projection Model," Technical Reports 97, Bank of Canada.
    11. 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).
    12. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    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. 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.
    15. repec:pri:cepsud:128sims is not listed on IDEAS
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    Citations

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    Cited by:

    1. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, Elsevier.
    2. Kamber, Gunes & McDonald, Chris & Sander, Nick & Theodoridis, Konstantinos, 2016. "Modelling the business cycle of a small open economy: The Reserve Bank of New Zealand's DSGE model," Economic Modelling, Elsevier, vol. 59(C), pages 546-569.
    3. Andrle, Michal, 2012. "Understanding DSGE Filters in Forecasting and Policy Analysis," Dynare Working Papers 16, CEPREMAP.
    4. Junior Maih, 2010. "Conditional forecasts in DSGE models," Working Paper 2010/07, Norges Bank.
    5. Mehdiyev, Mehdi & Ahmadov, Vugar & Huseynov, Salman & Mammadov, Fuad, 2015. "Ölkə iqtisadiyyatı üzrə göstəricilərin modelləşdirilməsi və proqnozlaşdırılması: problemlər və praktiki çətinliklər
      [Modeling and forecasting of macroeconomic variables of the national economy: pro
      ," MPRA Paper 63517, University Library of Munich, Germany.
    6. Andrew Binning & Junior Maih, 2016. "Forecast uncertainty in the neighborhood of the effective lower bound: How much asymmetry should we expect?," Working Paper 2016/13, Norges Bank.
    7. 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, Monetary Policy Group, Bank of Thailand.
    8. Güneş Kamber & Chris McDonald & Nicholas Sander & Konstantinos Theodoridis, 2015. "A structural model for policy analysis and forecasting: NZSIM," Reserve Bank of New Zealand Discussion Paper Series DP2015/05, Reserve Bank of New Zealand.
    9. 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.

    More about this item

    Keywords

    DSGE models; monetary policy; conditional forecasts;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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