Predicting turning points

Daniel M. Chin, John Geweke and Preston J. Miller

No 267, Staff Report from Federal Reserve Bank of Minneapolis

Abstract: This paper presents a new method for predicting turning points. The paper formally defines a turning point; develops a probit model for estimating the probability of a turning point; and then examines both the in-sample and out-of-sample forecasting performance of the model. The model performs better than some other methods for predicting turning points.

Keywords: Econometric; models (search for similar items in EconPapers)
Date: 2000
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
https://www.minneapolisfed.org/research/sr/sr267.pdf Full Text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fip:fedmsr:267

Access Statistics for this paper

More papers in Staff Report from Federal Reserve Bank of Minneapolis Contact information at EDIRC.
Bibliographic data for series maintained by Kate Hansel ().