IDEAS home Printed from https://ideas.repec.org/p/ptu/wpaper/w201114.html
   My bibliography  Save this paper

Rational vs. Professional Forecasts

Author

Listed:
  • João Valle e Azevedo
  • João Tovar Jalles

Abstract

We compare theoretical and empirical forecasts computed by rational agents living in a model economy to those produced by professional forecasters. We focus on the variance of the prediction errors as a function of the forecast horizon and analyze the speed with which it converges to a constant (which can be seen as a measure of the speed of convergence of the economy to the steady state). We look at a standard sticky-prices-wages model, concluding that it delivers a strong theoretical forecastability of the variables under scrutiny, at odds with the data (professional forecasts). The flexible prices-wages version delivers a forecastability closer to the data and performs relatively better empirically (with actual data), but mainly because forecasts deviate little from the unconditional mean. These results can be interpreted in at least two ways: first, actual deviations from the steady-state are not persistent, in which case the implications of the specific formulation of nominal rigidities for short-run dynamics are unrealistic; second, and still looking through the lens of a model, exogenous (or unmodelled) steady-state shifts attributable to, e.g., changes in monetary-policy, taxation, regulation or in the growth of the technological frontier, occur in such a way as to strongly limit the performance of professional forecasters.

Suggested Citation

  • João Valle e Azevedo & João Tovar Jalles, 2011. "Rational vs. Professional Forecasts," Working Papers w201114, Banco de Portugal, Economics and Research Department.
  • Handle: RePEc:ptu:wpaper:w201114
    as

    Download full text from publisher

    File URL: https://www.bportugal.pt/sites/default/files/anexos/papers/wp201114.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Fair, Ray C & Shiller, Robert J, 1989. "The Informational Context of Ex Ante Forecasts," The Review of Economics and Statistics, MIT Press, vol. 71(2), pages 325-331, May.
    2. Malin Adolfson & Jesper Linde & Mattias Villani, 2007. "Forecasting Performance of an Open Economy DSGE Model," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 289-328.
    3. Christiano, Lawrence J. & Trabandt, Mathias & Walentin, Karl, 2011. "Introducing financial frictions and unemployment into a small open economy model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 1999-2041.
    4. Engelberg, Joseph & Manski, Charles F. & Williams, Jared, 2009. "Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 30-41.
    5. Peter C.B. Phillips & Yixiao Sun & Sainan Jin, 2003. "Consistent HAC Estimation and Robust Regression Testing Using Sharp Origin Kernels with No Truncation," Cowles Foundation Discussion Papers 1407, Cowles Foundation for Research in Economics, Yale University.
    6. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    7. Victor Zarnowitz & Phillip Braun, 1993. "Twenty-two Years of the NBER-ASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 11-94, National Bureau of Economic Research, Inc.
    8. Peter N. Ireland, 2007. "Changes in the Federal Reserve's Inflation Target: Causes and Consequences," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(8), pages 1851-1882, December.
    9. Domenico Giannone & Michele Lenza & Lucrezia Reichlin, 2008. "Explaining The Great Moderation: It Is Not The Shocks," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 621-633, 04-05.
    10. Gavin, William T. & Mandal, Rachel J., 2003. "Evaluating FOMC forecasts," International Journal of Forecasting, Elsevier, vol. 19(4), pages 655-667.
    11. Adolfson, Malin & Laseen, Stefan & Linde, Jesper & Villani, Mattias, 2007. "Bayesian estimation of an open economy DSGE model with incomplete pass-through," Journal of International Economics, Elsevier, vol. 72(2), pages 481-511, July.
    12. 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.
    13. Antonello D'Agostino & Karl Whelan, 2008. "Federal Reserve Information During the Great Moderation," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 609-620, 04-05.
    14. Frank Schorfheide, 2005. "Learning and Monetary Policy Shifts," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 392-419, April.
    15. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    16. 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.
    17. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
    18. Victor Zarnowitz, 1992. "Business Cycles: Theory, History, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number zarn92-1.
    19. Tom Stark, 2010. "Realistic evaluation of real-time forecasts in the Survey of Professional Forecasters," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue May.
    20. 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.
    21. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    22. 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.
    23. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
    24. 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.
    25. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    26. Zarnowitz, Victor, 1992. "Business Cycles," National Bureau of Economic Research Books, University of Chicago Press, number 9780226978901, September.
    27. Stephen K. McNees, 1992. "How large are economic forecast errors?," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 25-42.
    28. Garcí­a, Juan Angel, 2003. "An introduction to the ECB's survey of professional forecasters," Occasional Paper Series 8, European Central Bank.
    29. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
    30. Bonham, Carl S & Cohen, Richard H, 2001. "To Aggregate, Pool, or Neither: Testing the Rational-Expectations Hypothesis Using Survey Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 278-291, July.
    31. David H. Romer & Christina D. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June.
    32. James H. Stock & Mark W. Watson, 1993. "Business Cycles, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number stoc93-1.
    33. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    34. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
    35. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    36. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
    37. Gamber, Edward N. & Smith, Julie K., 2009. "Are the Fed's inflation forecasts still superior to the private sector's?," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 240-251, June.
    38. Stock, James H. & Watson, Mark W. (ed.), 1993. "Business Cycles, Indicators, and Forecasting," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226774886, September.
    39. Faust, Jon & Wright, Jonathan H., 2008. "Efficient forecast tests for conditional policy forecasts," Journal of Econometrics, Elsevier, vol. 146(2), pages 293-303, October.
    40. Joutz, Fred & Stekler, H. O., 2000. "An evaluation of the predictions of the Federal Reserve," International Journal of Forecasting, Elsevier, vol. 16(1), pages 17-38.
    41. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    42. Gary S. Anderson & Andrew T. Levin & Eric T. Swanson, 2006. "Higher-order perturbation solutions to dynamic, discrete-time rational expectations models," Working Paper Series 2006-01, Federal Reserve Bank of San Francisco.
    43. Rubaszek, Michal & Skrzypczynski, Pawel, 2008. "On the forecasting performance of a small-scale DSGE model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 498-512.
    44. 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.
    45. Timothy Cogley & Argia M. Sbordone, 2008. "Trend Inflation, Indexation, and Inflation Persistence in the New Keynesian Phillips Curve," American Economic Review, American Economic Association, vol. 98(5), pages 2101-2126, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    2. repec:hal:spmain:info:hdl:2441/f4rshpf3v1umfa09lat09b1bg is not listed on IDEAS
    3. repec:spo:wpmain:info:hdl:2441/f4rshpf3v1umfa09lat09b1bg is not listed on IDEAS
    4. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    5. Paul Hubert, 2015. "Revisiting the Greenbook’s relative forecasting performance," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(1), pages 151-179.
    6. Kolasa, Marcin & Rubaszek, Michał, 2015. "Forecasting using DSGE models with financial frictions," International Journal of Forecasting, Elsevier, vol. 31(1), pages 1-19.
    7. repec:spo:wpecon:info:hdl:2441/f4rshpf3v1umfa09lat09b1bg is not listed on IDEAS
    8. Paul Hubert, 2015. "Do Central Bank Forecasts Influence Private Agents? Forecasting Performance versus Signals," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(4), pages 771-789, June.
    9. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    10. repec:hal:wpspec:info:hdl:2441/f4rshpf3v1umfa09lat09b1bg is not listed on IDEAS
    11. repec:hal:spmain:info:hdl:2441/35kgubh40v9gfpnuruelqjnptb is not listed on IDEAS
    12. repec:spo:wpmain:info:hdl:2441/35kgubh40v9gfpnuruelqjnptb is not listed on IDEAS
    13. Marcin Kolasa & Michał Rubaszek & Paweł Skrzypczyński, 2012. "Putting the New Keynesian DSGE Model to the Real‐Time Forecasting Test," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1301-1324, October.
    14. Bekiros Stelios & Paccagnini Alessia, 2015. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.
    15. Clements, Michael P, 2012. "Subjective and Ex Post Forecast Uncertainty : US Inflation and Output Growth," The Warwick Economics Research Paper Series (TWERPS) 995, University of Warwick, Department of Economics.
    16. 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.
    17. Clements, Michael P. & Galvão, Ana Beatriz, 2017. "Model and survey estimates of the term structure of US macroeconomic uncertainty," International Journal of Forecasting, Elsevier, vol. 33(3), pages 591-604.
    18. Paul Hubert, 2010. "Monetary policy, imperfect information and the expectations channel [Politique monétaire,information imparfaite et canal des anticipations]," SciencePo Working papers Main tel-04095385, HAL.
    19. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.
    20. Volker Wieland & Maik Wolters, 2011. "The diversity of forecasts from macroeconomic models of the US economy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 47(2), pages 247-292, June.
    21. Franke, Reiner & Jang, Tae-Seok & Sacht, Stephen, 2015. "Moment matching versus Bayesian estimation: Backward-looking behaviour in a New-Keynesian baseline model," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 126-154.
    22. Clements, Michael P., 2010. "Why are survey forecasts superior to model forecasts?," Economic Research Papers 270770, University of Warwick - Department of Economics.
    23. Liu, Dandan & Smith, Julie K., 2014. "Inflation forecasts and core inflation measures: Where is the information on future inflation?," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 133-137.
    24. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    25. Bekiros, Stelios D. & Paccagnini, Alessia, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 298-323.
    26. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ptu:wpaper:w201114. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: DEE-NTD (email available below). General contact details of provider: https://edirc.repec.org/data/bdpgvpt.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.