Journal of Business Cycle Measurement and Analysis

Frequency
3 times a year
ISSN: 
1729-3626 (online)
ISSN: 
1729-3618 (print)
http://dx.doi.org/10.1787/17293626
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The Journal of Business Cycle Measurement and Analysis has been discontinued as of 24 June 2016. This journal was published jointly with CIRET from 2004 to 2015. For more information see www.ciret.org/jbcy.

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Macroeconomic Forecasting

Debunking a Few Old Wives' Tales You do not have access to this content

English
 
Click to Access: 
    http://oecd.metastore.ingenta.com/content/3307031ec002.pdf
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Author(s):
Stefano Siviero, Daniele Terlizzese
22 July 2008
Pages:
30
Bibliographic information
No.:
15,
Volume:
2007,
Issue:
3
Pages:
287–316
http://dx.doi.org/10.1787/jbcma-v2007-art14-en

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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.

 
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