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Using forecast evaluation to improve the accuracy of the Greenbook forecast

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  • Arai, Natsuki

Abstract

Recently, Patton and Timmermann (2012) proposed a more powerful kind of forecast efficiency regression at multiple horizons, and showed that it provides evidence against the efficiency of the Fed’s Greenbook forecasts. I use their forecast efficiency evaluation to propose a method for adjusting the Greenbook forecasts. Using this method in a real-time out-of-sample forecasting exercise, I find that it provides modest improvements in the accuracies of the forecasts for the GDP deflator and CPI, but not for other variables. The improvements are statistically significant in some cases, with magnitudes of up to 18% in root mean square prediction error.

Suggested Citation

  • Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    • Handle: RePEc:eee:intfor:v:30:y:2014:i:1:p:12-19
    DOI: 10.1016/j.ijforecast.2013.02.002
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    References listed on IDEAS

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    1. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    2. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
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    4. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.
    5. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
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    7. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
    8. 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.
    9. Peter Tulip, 2009. "Has the Economy Become More Predictable? Changes in Greenbook Forecast Accuracy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1217-1231, September.
    10. Croushore, Dean, 2006. "Forecasting with Real-Time Macroeconomic Data," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 17, pages 961-982, Elsevier.
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    13. Rochelle M. Edge & Refet S. Gurkaynak, 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 41(2 (Fall)), pages 209-259.
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    Cited by:

    1. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    2. Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.
    3. Natsuki Arai, 2016. "Evaluating the Efficiency of the FOMC's New Economic Projections," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 1019-1049, August.
    4. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    5. Levent Bulut, 2017. "Does Statistical Significance Help to Evaluate Predictive Performance of Competing Models?," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 1(1), pages 1-13.
    6. Arai, Natsuki & Iizuka, Nobuo & Yamamoto, Yohei, 2022. "The Efficiency of the Government’s Revenue Projections," Discussion paper series HIAS-E-122, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    7. Andrew C. Chang & Tyler J. Hanson, 2015. "The Accuracy of Forecasts Prepared for the Federal Open Market Committee," Finance and Economics Discussion Series 2015-62, Board of Governors of the Federal Reserve System (U.S.).
    8. Andrew C. Chang, 2018. "The Fed's Asymmetric Forecast Errors," Finance and Economics Discussion Series 2018-026, Board of Governors of the Federal Reserve System (U.S.).
    9. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.

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