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Conditional versus unconditional forecasting with the New Area-Wide Model of the euro area

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  • Christoffel, Kai
  • Coenen, Gunter
  • Warne, Anders

Abstract

In this paper we examine conditional versus unconditional forecasting with a version of the New Area-Wide Model (NAWM) of the euro area designed for use in the context of the macroeconomic projection exercises at the European Central Bank (ECB). We first analyse the out-of-sample forecasting properties of the estimated model from 1999 to 2005 by comparing its unconditional forecasts with those obtained from a Bayesian VAR with a steady-state prior as well as na¨ıve forecasts. Model-based forecasts that are conditioned on differing information sets are then studied and evaluated through, for instance, modesty statistics to assess the relevance of the Lucas critique. In contrast to other studies in the literature, we condition on a fairly large set of policy-relevant variables. Furthermore, we consider conditioning information that partially, albeit not fully determine the future path of the observed variables, but which restrict the channels through which they can be affected.

Suggested Citation

  • Christoffel, Kai & Coenen, Gunter & Warne, Anders, 2007. "Conditional versus unconditional forecasting with the New Area-Wide Model of the euro area," MPRA Paper 76759, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:76759
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    2. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    3. Ian Christensen & Paul Corrigan & Caterina Mendicino & Shin‐Ichi Nishiyama, 2016. "Consumption, housing collateral and the Canadian business cycle," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(1), pages 207-236, February.
    4. Malte Knüppel & Guido Schultefrankenfeld, 2017. "Interest rate assumptions and predictive accuracy of central bank forecasts," Empirical Economics, Springer, vol. 53(1), pages 195-215, August.
    5. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2008. "How Structural Are Structural Parameters?," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 83-137, National Bureau of Economic Research, Inc.
    6. Barbara Rudolf & Mathias Zurlinden, 2014. "A compact open economy DSGE model for Switzerland," Economic Studies 2014-08, Swiss National Bank.
    7. Oana Simona HUDEA, 2016. "The New Keynesian Theory And Its Associated Model," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 8, pages 151-159, December.
    8. Tovar, Camilo Ernesto, 2009. "DSGE Models and Central Banks," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 3, pages 1-31.
    9. Rodríguez, Aldo, 2020. "Estimación Bayesiana de un Modelo de Economía Abierta con Sector Bancario," Dynare Working Papers 52, CEPREMAP.
    10. M. Woodford., 2010. "Convergence in Macroeconomics: Elements of the New Synthesis," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 10.
    11. Igor Vetlov & Ricardo Mourinho Felix & Laure Frey & Tibor Hledik & Zoltan Jakab & Niki Papadopoulou & Lukas Reiss & Martin Schneider, 2010. "The Implementation of Scenarios using DSGE Models," Working Papers 2010-10, Central Bank of Cyprus.
    12. Ingvar Strid & Karl Walentin, 2009. "Block Kalman Filtering for Large-Scale DSGE Models," Computational Economics, Springer;Society for Computational Economics, vol. 33(3), pages 277-304, April.
    13. Coenen, Günter & Mohr, Matthias & Straub, Roland, 2008. "Fiscal consolidation in the euro area: Long-run benefits and short-run costs," Economic Modelling, Elsevier, vol. 25(5), pages 912-932, September.
    14. Junior Maih, 2010. "Conditional forecasts in DSGE models," Working Paper 2010/07, Norges Bank.
    15. Jesús Fernández-Villaverde, 2008. "Horizons of Understanding: A Review of Ray Fair's Estimating How the Macroeconomy Works," Journal of Economic Literature, American Economic Association, vol. 46(3), pages 685-703, September.

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    More about this item

    Keywords

    DSGE modelling; open-economy macroeconomics; Bayesian inference; forecasting; euro area;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • 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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