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Evaluating UK point and density forecasts from an estimated DSGE model: the role of off-model information over the financial crisis

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  • Fawcett, Nicholas

    (Bank of England)

  • Koerber, Lena

    (Bank of England)

  • Masolo, Riccardo

    (Bank of England)

  • Waldron, Matthew

    (Bank of England)

Abstract

This paper investigates the real-time forecast performance of the Bank of England’s main DSGE model, COMPASS, before, during and after the financial crisis with reference to statistical and judgemental benchmarks. A general finding is that COMPASS’s relative forecast performance improves as the forecast horizon is extended (as does that of the Statistical Suite of forecasting models). The performance of forecasts from all three sources deteriorates substantially following the financial crisis. The deterioration is particularly marked for the DSGE model’s GDP forecasts. One possible explanation for that, and a key difference between DSGE models and judgemental forecasts, is that judgemental forecasts are implicitly conditioned on a broader information set, including faster-moving indicators that may be particularly informative when the state of the economy is evolving rapidly, as in periods of financial distress. Consistent with that interpretation, GDP forecasts from a version of the DSGE model augmented to include a survey measure of short-term GDP growth expectations are competitive with the judgemental forecasts at all horizons in the post-crisis period. More generally, a key theme of the paper is that both the type of off-model information and the method used to apply it are key determinants of DSGE model forecast accuracy.

Suggested Citation

  • Fawcett, Nicholas & Koerber, Lena & Masolo, Riccardo & Waldron, Matthew, 2015. "Evaluating UK point and density forecasts from an estimated DSGE model: the role of off-model information over the financial crisis," Bank of England working papers 538, Bank of England.
  • Handle: RePEc:boe:boeewp:0538
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    as
    1. Ferroni Filippo, 2011. "Trend Agnostic One-Step Estimation of DSGE Models," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-36, July.
    2. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    3. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    4. Barnett, Alina & Batten, Sandra & Chiu, Adrian & Franklin, Jeremy & Sebastia-Barriel, Maria, 2014. "The UK productivity puzzle," Bank of England Quarterly Bulletin, Bank of England, vol. 54(2), pages 114-128.
    5. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-474, October.
    6. 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.
    7. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    8. Diego Comin & Mark Gertler, 2006. "Medium-Term Business Cycles," American Economic Review, American Economic Association, vol. 96(3), pages 523-551, June.
    9. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
    10. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    11. Giacomini, Raffaella & Ragusa, Giuseppe, 2011. "Incorporating theoretical restrictions into forecasting by projection methods," CEPR Discussion Papers 8604, C.E.P.R. Discussion Papers.
    12. Kapetanios, George & Labhard, Vincent & Price, Simon, 2008. "Forecast combination and the Bank of England's suite of statistical forecasting models," Economic Modelling, Elsevier, vol. 25(4), pages 772-792, July.
    13. Maik H. Wolters, 2015. "Evaluating Point and Density Forecasts of DSGE Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 74-96, January.
    14. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    15. Wolters, Maik H., 2011. "Forecasting under Model Uncertainty," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48723, Verein für Socialpolitik / German Economic Association.
    16. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    17. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    18. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    19. Nicholas Oulton & María Sebastiá-Barriel, 2013. "Long and Short-Term Effects of the Financial Crisis on Labour Productivity, Capital and Output," CEP Discussion Papers dp1185, Centre for Economic Performance, LSE.
    20. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809.
    21. Joyce, Michael & Tong, Matthew & Woods, Robert, 2011. "The United Kingdom’s quantitative easing policy: design, operation and impact," Bank of England Quarterly Bulletin, Bank of England, vol. 51(3), pages 200-212.
    22. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
    23. repec:wop:calsdi:96-17 is not listed on IDEAS
    24. Wouter Denhaan & Andrew T. Levin, 1996. "VARHAC Covariance Matrix Estimator (GAUSS)," QM&RBC Codes 64, Quantitative Macroeconomics & Real Business Cycles.
    25. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    26. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
    27. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2010. "A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 720-754.
    28. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, September.
    29. Burgess, Stephen & Fernandez-Corugedo, Emilio & Groth, Charlotta & Harrison, Richard & Monti, Francesca & Theodoridis, Konstantinos & Waldron, Matt, 2013. "The Bank of England's forecasting platform: COMPASS, MAPS, EASE and the suite of models," Bank of England working papers 471, Bank of England.
    30. Hackworth, Christopher & Radia, Amar & Roberts, Nyssa, 2013. "Understanding the MPC’s forecast performance since mid-2010," Bank of England Quarterly Bulletin, Bank of England, vol. 53(4), pages 336-350.
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    3. Paloviita, Maritta & Haavio, Markus & Jalasjoki, Pirkka & Kilponen, Juha & Vänni, Ilona, 2020. "Reading between the lines : Using text analysis to estimate the loss function of the ECB," Research Discussion Papers 12/2020, Bank of Finland.
    4. Boneva, Lena & Fawcett, Nicholas & Masolo, Riccardo M. & Waldron, Matt, 2019. "Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 100-120.
    5. Cai, Michael & Del Negro, Marco & Giannoni, Marc P. & Gupta, Abhi & Li, Pearl & Moszkowski, Erica, 2019. "DSGE forecasts of the lost recovery," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1770-1789.
    6. Iversen, Jens & Laséen, Stefan & Lundvall, Henrik & Söderström, Ulf, 2016. "Real-Time Forecasting for Monetary Policy Analysis: The Case of Sveriges Riksbank," Working Paper Series 318, Sveriges Riksbank (Central Bank of Sweden).
    7. Papavangjeli, Meri & Rama, Arlind, 2018. "A statistical evaluation of GAP's forecasting performance for the Albanian economy," MPRA Paper 116104, University Library of Munich, Germany.
    8. Nasir, Muhammad Ali, 2020. "Forecasting inflation under uncertainty: The forgotten dog and the frisbee," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    9. David F Hendry & John N J Muellbauer, 2018. "The future of macroeconomics: macro theory and models at the Bank of England," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(1-2), pages 287-328.
    10. Alex Haberis & Riccardo M. Masolo & Kate Reinold, 2019. "Deflation Probability and the Scope for Monetary Loosening in the United Kingdom," International Journal of Central Banking, International Journal of Central Banking, vol. 15(1), pages 233-277, March.
    11. Kapetanios, George & Millard, Stephen & Price, Simon & Petrova, Katerina, 2018. "Time varying cointegration and the UK Great Ratios," Essex Finance Centre Working Papers 23320, University of Essex, Essex Business School.
    12. repec:zbw:bofrdp:2021_007 is not listed on IDEAS
    13. Clements, Michael P. & Reade, J. James, 2020. "Forecasting and forecast narratives: The Bank of England Inflation Reports," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1488-1500.
    14. Kapetanios, George & Masolo, Riccardo M. & Petrova, Katerina & Waldron, Matthew, 2019. "A time-varying parameter structural model of the UK economy," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
    15. J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
    16. Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.
    17. Cardani, Roberta & Paccagnini, Alessia & Villa, Stefania, 2019. "Forecasting with instabilities: An application to DSGE models with financial frictions," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    18. Eleonora Granziera & Pirkka Jalasjoki & Maritta Paloviita, 2021. "The Bias and Efficiency of the ECB Inflation Projections: a State Dependent Analysis," Working Paper 2021/1, Norges Bank.
    19. repec:zbw:bofrdp:2020_012 is not listed on IDEAS
    20. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2021. "The bias and efficiency of the ECB inflation projections: A state dependent analysis," Bank of Finland Research Discussion Papers 7/2021, Bank of Finland.
    21. Domit, Sílvia & Monti, Francesca & Sokol, Andrej, 2019. "Forecasting the UK economy with a medium-scale Bayesian VAR," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1669-1678.
    22. Kapetanios, George & Price, Simon & Theodoridis, Konstantinos, 2015. "A new approach to multi-step forecasting using dynamic stochastic general equilibrium models," Economics Letters, Elsevier, vol. 136(C), pages 237-242.
    23. Domit, Sílvia & Monti, Francesca & Sokol, Andrej, 2016. "A Bayesian VAR benchmark for COMPASS," Bank of England working papers 583, Bank of England.

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    More about this item

    Keywords

    DSGE models; forecasting; financial crisis.;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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