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One model and various experts: Evaluating Dutch macroeconomic forecasts

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  • Franses, Philip Hans
  • Kranendonk, Henk C.
  • Lanser, Debby

Abstract

The Netherlands Bureau for Economic Policy Analysis (CPB) uses a large macroeconomic model to create forecasts of various important macroeconomic variables. The outcomes of this model are usually filtered by experts, and it is the expert forecasts that are made available to the general public. In this paper we re-create the model forecasts for the period 1997-2008 and compare the expert forecasts with the pure model forecasts. Our key findings from the first time that this unique database has been analyzed are that (i) experts adjust upwards more often; (ii) expert adjustments are not autocorrelated, but their sizes do depend on the value of the model forecast; (iii) the CPB model forecasts are biased for a range of variables, but (iv) at the same time, the associated expert forecasts are more often unbiased; and that (v) expert forecasts are far more accurate than the model forecasts, particularly when the forecast horizon is short. In summary, the final CPB forecasts de-bias the model forecasts and lead to higher accuracies than the initial model forecasts.

Suggested Citation

  • Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495, April.
  • Handle: RePEc:eee:intfor:v:27:y::i:2:p:482-495
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    References listed on IDEAS

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    1. Henk Don, 2004. "How econometric models help policy makers; theory and practice," CPB Discussion Paper 27, CPB Netherlands Bureau for Economic Policy Analysis.
    2. Philip Hans Franses & Rianne Legerstee, 2010. "Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 331-340.
    3. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    4. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    5. Goodwin, Paul, 2000. "Improving the voluntary integration of statistical forecasts and judgment," International Journal of Forecasting, Elsevier, vol. 16(1), pages 85-99.
    6. F. J. H. Don & J. P. Verbruggen, 2006. "Models and methods for economic policy: 60 years of evolution at CPB," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(2), pages 145-170.
    7. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    8. O'Connor, Marcus & Remus, William & Griggs, Ken, 1993. "Judgemental forecasting in times of change," International Journal of Forecasting, Elsevier, vol. 9(2), pages 163-172, August.
    9. Robert Fildes & Paul Goodwin, 2007. "Good and Bad Judgment in Forecasting: Lessons from Four Companies," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 5-10, Fall.
    10. Franses, Philip Hans & Legerstee, Rianne, 2009. "Properties of expert adjustments on model-based SKU-level forecasts," International Journal of Forecasting, Elsevier, vol. 25(1), pages 35-47.
    11. Robert C. Blattberg & Stephen J. Hoch, 1990. "Database Models and Managerial Intuition: 50% Model + 50% Manager," Management Science, INFORMS, vol. 36(8), pages 887-899, August.
    12. Henk Kranendonk & Johan Verbruggen, 2007. "SAFFIER; a multi-purpose model of the Dutch economy for short-term and medium-term analyses," CPB Document 144, CPB Netherlands Bureau for Economic Policy Analysis.
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    Citations

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    Cited by:

    1. Bolger, Fergus & Wright, George, 2017. "Use of expert knowledge to anticipate the future: Issues, analysis and directions," International Journal of Forecasting, Elsevier, vol. 33(1), pages 230-243.
    2. Chang, Chia-Lin & de Bruijn, Bert & Franses, Philip Hans & McAleer, Michael, 2013. "Analyzing fixed-event forecast revisions," International Journal of Forecasting, Elsevier, vol. 29(4), pages 622-627.
    3. Simionescu, Mihaela, 2014. "New Strategies to Improve the Accuracy of Predictions based on Monte Carlo and Bootstrap Simulations: An Application to Bulgarian and Romanian Inflation || Nuevas estrategias para mejorar la exactitud," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 18(1), pages 112-129, December.
    4. repec:spr:soinre:v:135:y:2018:i:1:d:10.1007_s11205-016-1490-3 is not listed on IDEAS
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    6. repec:eee:ecmode:v:68:y:2018:i:c:p:506-513 is not listed on IDEAS
    7. repec:wly:ijfiec:v:22:y:2017:i:1:p:3-11 is not listed on IDEAS
    8. Chang, Chia Lin & Franses, Philip Hans & Mcaleer, Michael, 2012. "Evaluating Individual and Mean Non-Replicable Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-43, September.
    9. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents' expectations. Different patterns of anticipation of the 2008 financial crisis”," IREA Working Papers 201511, University of Barcelona, Research Institute of Applied Economics, revised Mar 2015.
    10. Nibbering, Didier & Paap, Richard & van der Wel, Michel, 2018. "What do professional forecasters actually predict?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 288-311.
    11. repec:spr:qualqt:v:51:y:2017:i:6:d:10.1007_s11135-016-0416-0 is not listed on IDEAS
    12. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    13. Volha Audzei, 2016. "Confidence Cycles and Liquidity Hoarding," Working Papers 2016/07, Czech National Bank, Research Department.
    14. Fildes, Robert, 2015. "Forecasters and rationality—A comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 140-143.
    15. Philip Franses, 2014. "Evaluating CPB’s Forecasts," De Economist, Springer, vol. 162(3), pages 215-221, September.
    16. Philip Hans Franses & Bert Bruijn, 2017. "Benchmarking Judgmentally Adjusted Forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 3-11, January.
    17. Simionescu, Mihaela, 2015. "A Comparative Analysis Of Macroeconomic Forecasts Accuracy In Spain And Romania," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 6(1), pages 67-74.

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