Abstract
AbstractIn this paper we examine the consistency in the timing of crisis events of the most prominent databases of banking and fiscal crises. We calculate Cohen's kappa measure, utilize signaling approach and panel logit models with random effects on selected early warning indicators and identify the most influential crisis observations using the Pregibon's delta‐beta influence statistics. Our results confirm that the degree of commonality across databases is indeed relatively high, especially if introducing a 1‐year lag. However, there is still a significant role played by a few influential observations. This problem is more pronounced in the banking crisis literature.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
