Financial Crises: Explanations, Types, and Implications; by Stijn Claessens and M. Ayhan Kose; imf working Paper 13/28; January 1, 2013

IV.   I

DENTIFICATION

,

 

D

ATING AND 

F

REQUENCY OF 

C

RISES

 

A large body of work has been devoted to the identification and dating of crises, but 

ambiguities remain. Methodologies based on the main theories explaining various types of 

crises can be used to identify (and accordingly classify) crises.

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 In practice, however, this is 

not straightforward. While currency (and inflation) crises and sudden stops lend themselves 

to quantitative approaches, the dating of debt and banking crises is typically based on 

qualitative and judgmental analyses. Irrespective of type, variations in methodologies can 

lead to differences in the start and end dates of crises. And, as noted, various types of crises 

can overlap in a single episode, creating possible ambiguities as to how to classify the 

episode.  

 

This in part because the frequency and types of financial crises have evolved over time. In 

practice, a wide range of quantitative and qualitative methods involving judgment are used to 

identify and classify crises. The data also shows that crises have evolved over time. For 

example, currency crises were dominant during the 1980s whereas banking crises and sudden 

stops became more prevalent in the 1990s and 2000s. This section begins with a summary of 

common identification and dating methods (see also IMF WEO 1998; Reinhart and Rogoff, 

2009a; and Laeven and Valencia, 2008, 2012). It then provides a summary of the frequency 

of crises over time, across groups of countries, and the overlap among types of crises.  

                                                 

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 Specifically, there was an increase in real estate prices in many markets around the world, 

paralleled by a run-up in other asset prices, especially in equity. Reinhart and Rogoff (2008) 

demonstrate that the appreciation of equity and house prices in the U.S. before the crisis was even 

more dramatic than appreciations experienced before the “Big Five” post-war debt crises. As the 

global crisis unfolded, those countries that had experienced the greatest increases in equity and house 

prices during the boom found themselves most vulnerable (see Feldstein, 2009, and Teslik, 2009). 

Unfortunately, the similarity in crises patterns was, as is often the case, only recognized ex-post.

 

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 Dating does not of course establish causes, including whether the event was a rational outcome to 

some other “cause” (e.g., a crash in an asset price may be rational in response to a real shock or not). 

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