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Macroeconomic Forecasting: Debunking a Few Old Wives' Tales

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  • Stefano Siviero

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  • Daniele Terlizzese

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Abstract

The forecasting profession, especially when producing forecasts intended to support economic policy, does not currently enjoy a good reputation. Complaints are sometimes voiced about its lack of scientific discipline, which in turn implies that the forecast results may be viewed as arbitrary. At other times, it is the excessively mechanical nature of the forecasting process which is criticised, on the grounds that it prevents a proper evaluation of any information concerning changes that alter the functioning of the economic system. Moreover, the use of structural models is often deemed superfluous, or even dangerous, and reduced forms are suggested as a preferable alternative. Drawing on the actual forecasting experience at the Bank of Italy, this paper argues that these views stem largely from a biased perception of how forecasting works, what it consists of and which goals it pursues. In particular, forecasting does not simply amount to producing a set of figures: rather, it aims at assembling a fullyfledged view – one may call it a "story behind the figures" – of what could happen: a story that has to be internally consistent, whose logical plausibility can be assessed, whose structure is sufficiently articulated to allow one to make a systematic comparison with the wealth of information that accumulates as time goes by. This implies that the forecasts are not the result of a black-box process that completely lacks discipline; neither are they the outcome of a purely mechanical process that cannot take new information into account. This paper tries to show that forecasting can be rigorous, not mechanical, informative, and useful even in the face of unprecedented situations.

Suggested Citation

  • Stefano Siviero & Daniele Terlizzese, 2008. "Macroeconomic Forecasting: Debunking a Few Old Wives' Tales," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2007(3), pages 287-316.
  • Handle: RePEc:oec:stdkaa:5kzdnhzqhzs0
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    File URL: http://dx.doi.org/10.1787/jbcma-v2007-art14-en
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    References listed on IDEAS

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    1. Raffaele Miniaci & Guglielmo Weber, 1999. "The Italian Recession Of 1993: Aggregate Implications Of Microeconomic Evidence," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 237-249, May.
    2. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics,in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148 Elsevier.
    3. Stefano Siviero & Daniele Terlizzese & Ignazio Visco, 1999. "Are model-based inflation forecasts used in monetary policymaking? A case study," Temi di discussione (Economic working papers) 357, Bank of Italy, Economic Research and International Relations Area.
    4. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    5. Favero, C. & Hendry, D., 1990. "Testing The Lucas Critique: A Review," Economics Series Working Papers 99101, University of Oxford, Department of Economics.
    6. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
    7. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    8. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    9. Christopher A. Sims, 1982. "Policy Analysis with Econometric Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 13(1), pages 107-164.
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    Cited by:

    1. Fabio Busetti, 2001. "The use of preliminary data in econometric forecasting: an application with the Bank of Italy Quarterly Model," Temi di discussione (Economic working papers) 437, Bank of Italy, Economic Research and International Relations Area.
    2. Matteo Bugamelli & Patrizio Pagano, 2004. "Barriers to investment in ICT," Applied Economics, Taylor & Francis Journals, vol. 36(20), pages 2275-2286.
    3. Luca Dedola & Eugenio Gaiotti & Luca Silipo, 2001. "Money demand in the euro area: do national differences matter?," Temi di discussione (Economic working papers) 405, Bank of Italy, Economic Research and International Relations Area.
    4. Michele Caivano & Lisa Rodano & Stefano Siviero, 2010. "The transmission of the global financial crisis to the Italian economy. A counterfactual analysis, 2008-2010," Questioni di Economia e Finanza (Occasional Papers) 64, Bank of Italy, Economic Research and International Relations Area.
    5. Guido Bulligan & Fabio Busetti & Michele Caivano & Pietro Cova & Davide Fantino & Alberto Locarno & Lisa Rodano, 2017. "The Bank of Italy econometric model: an update of the main equations and model elasticities," Temi di discussione (Economic working papers) 1130, Bank of Italy, Economic Research and International Relations Area.
    6. Jennifer Castle & David Hendry, 2016. "Policy Analysis, Forediction, and Forecast Failure," Economics Series Working Papers 809, University of Oxford, Department of Economics.
    7. Ricardo Mestre & Peter McAdam, 2011. "Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 303-324, April.
    8. repec:gam:jecnmx:v:5:y:2017:i:3:p:39-:d:110547 is not listed on IDEAS

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    Keywords

    Forecasting; Policy-making;

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