Table III provides the frequency distribution of our sample with respect to distress and closure. Almost 42 percent of the institutions in our sample experienced distress, while by July 1999 only 82 of the 120 distressed institutions survived with some type of assistance. Of the whole sample, 38 out of 283 institutions in existence in July 1997, or 13 percent, were closed over this period. Indonesia is the country with the most financial system distress, in terms of absolute numbers of distressed and closed institutions, followed by Korea and Thailand, but the rank is the opposite in terms of the percentage of institutions in distress (Table IV). Malaysia has fewer distressed institutions and did not close any financial institution. The Philippines has the least distressed institutions, four, but did close two nonbank institutions.

We use only financial information as of the end of 1996-the year preceding the crisis-thus avoiding any risk of contaminating our estimations with the occurrence of distress and closure processes themselves.1<sup>2</sup> We collect end-1996 financial data for the different dimensions of a CAMEL-type risk analysis, as used by supervisors in many countries. Table V lists the independent variables, their corresponding CAMELcategories and their definition. Some CAMEL variables were not available for all countries. For instance, two indicators of financial institution risk, the ratio of nonperforming loans to total loans and the capital risk-adjusted adequacy ratio, were not available in a consistent manner for all the five countries under study.'<sup>3</sup> We end up using the following variables: equity to gross loans, loan loss reserves to capital, loan growth, operational expenses to revenues, return on assets, net interest revenues as a share of total revenues, and loans to borrowings. Although not strictly a CAMEL variable, size has usually been added in early warning studies as a proxy for "too big to fail" situations.'<sup>4</sup> In the specific case of the East Asian countries, following Kane (1998), we hypothesize that larger institutions are more likely to be subject to political intervention and links, 12 In particular, by using 1996-only data we avoid our estimations describing the behavior of supervisors, rather than the possibilities of impending distress. If we would have used later data, the estimations might have captured, for example, the fact that supervisors consider those financial institutions distressed which have low capitalization. At the same time, using 1996-only data is a strict criteria as for several countries the financial crisis was worse in 1998 than in 1997, and distress for some financial institutions only occurred in 1998. For that reasons, we could have used in some case also 1997 data. Also, the decision to close distressed financial institutions occurred largely in 1998, meaning we could have used 1997 data to analyze the importance of the financial condition of individual financial institutions at end-1997 in 1998 closure decisions. Furthermore, to account for differences across countries and periods, we could have added macroeconomic variables, such as GDP-declines, to explain the relative occurrence of distress. More generally, we could have estimated a cumulative distress (hazard) model, as is often done by bank supervisors in developed countries. On all these accounts, the use of 1996-only data biases our analysis against finding strong results.

**13** Definitions of non-performing loans varied widely across countries, and banks were given considerably leeway before the crisis in classifying loans. While all countries had capital adequacy requirements, the definitions of allowable sources of capital differed across countries.

**14** We would have like to use as well data on financial institutions' exposures to risky sectors (e.g., real estate or lending for securities markets) and possible maturity mismatches (foreign exchange, interest), but these data were not available for all countries on a comparable basis,

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