A Bayesian Signals Approach for the Detection of Crises

Panayotis Michaelides, Mike Tsionas and Panos Xidonas ()
Additional contact information
Panos Xidonas: ESSCA Business School

Journal of Quantitative Economics, 2020, vol. 18, issue 3, No 4, 585 pages

Abstract: Abstract In this paper, we consider the signals approach as an early-warning-system to detect crises. Crisis detection from a signals approach involves Type I and II errors which are handled through a utility function. We provide a Bayesian model and we test the effectiveness of the signals approach in three data sets: (1) Currency and banking crises for 76 currency and 26 banking crises in 15 developing and 5 industrial countries between 1970 and 1995, (2) costly asset price booms using quarterly data ranging from 1970 to 2007, and (3) public debt crises in Europe in 11 countries in the European Monetary Union from the introduction of the Euro until November 2011. The Bayesian model relies on a vector autoregression for indicator variables, and incorporates dynamic factors, time-varying weights in the latent composite indicator and special priors to avoid the proliferation of parameters. The Bayesian vector autoregressions are extended to a semi-parametric context to capture non-linearities. Our evidence reveals that our approach is successful as an early-warning mechanism after allowing for breaks and nonlinearities and, perhaps more importantly, the composite indicator is better represented as a flexible nonlinear function of the underlying indicators.

Keywords: Predicting crises; Early warning system; Bayesian analysis; Leading indicators (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s40953-019-00186-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:jqecon:v:18:y:2020:i:3:d:10.1007_s40953-019-00186-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40953

DOI: 10.1007/s40953-019-00186-8

Access Statistics for this article

Journal of Quantitative Economics is currently edited by Dilip Nachane and P.G. Babu

More articles in Journal of Quantitative Economics from Springer, The Indian Econometric Society (TIES) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().