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Calling recessions in real time

Author: James D Hamilton; National Bureau of Economic Research.
Publisher: Cambridge, Mass. : National Bureau of Economic Research, ©2010.
Series: Working paper series (National Bureau of Economic Research), no. 16162.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This paper surveys efforts to automate the dating of business cycle turning points. Doing this on a real time, out-of-sample basis is a bigger challenge than many academics might presume due to factors such as data revisions and changes in economic relationships over time. The paper stresses the value of both simulated real-time analysis-- looking at what the inference of a proposed model would have been using data  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: James D Hamilton; National Bureau of Economic Research.
OCLC Number: 646022553
Description: 1 online resource (50 pages) : illustrations.
Series Title: Working paper series (National Bureau of Economic Research), no. 16162.
Responsibility: James D. Hamilton.

Abstract:

This paper surveys efforts to automate the dating of business cycle turning points. Doing this on a real time, out-of-sample basis is a bigger challenge than many academics might presume due to factors such as data revisions and changes in economic relationships over time. The paper stresses the value of both simulated real-time analysis-- looking at what the inference of a proposed model would have been using data as they were actually released at the time-- and actual real-time analysis, in which a researcher stakes his or her reputation on publicly using the model to generate out-of-sample, real-time predictions. The immediate publication capabilities of the internet make the latter a realistic option for researchers today, and many are taking advantage of it. The paper reviews a number of approaches to dating business cycle turning points and emphasizes the fundamental trade-off between parsimony-- trying to keep the model as simple and robust as possible-- and making full use of available information. Different approaches have different advantages, and the paper concludes that there may be gains from combining the best features of several different approaches.

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