from the country (Sachs and Woo, 2000). This tendency should be more pronounced in private capital rather than public capital, as public capital often flows into a country in the form of international rescue package when a country faces financial crises. In this sense, operationally, capital flight statistics can be used as an indicator. The core of calculating capital flight is net errors and omissions plus non-FDI net private flows in balance of payments (Loungani and Mauro, 2001). One issue is whether to include current transfer in the current account, since this item includes private remittance (Caves, Frankel and Jones, 1996). The decision whether to include the current transfer sometimes makes significant differences on the crisis identification. For example, the inclusion of the current transfer cannot identify the 2001 Argentina as financial crises,<sup>(9)</sup> while the exclusion identifies the periods as financial crises. As the 2001 Argentina crisis is often characterized as abrupt capital outflows, the current transfer is excluded from capital flight.

# **2.4 Data and Methodology**

The main data sources are the IMF’s International Financial Statistics (IFS), the World Bank’s Global Development Finance (GDF), World Development Indicators (WDI) and CEIC Asian economic database. Seven crisis types (liquidity type banking, solvency type banking, balance of payments, currency, debt, growth rate and financial crises) in 15 emerging economies between Q1 1980 and Q4 2002 are examined on a quarterly basis based on the operational definitions. The fifteen countries are selected based on regional diversification, frequencies in appearing in existing crisis studies and data availability. These countries are: five East Asian (Indonesia, Korea, Malaysia, the Philippines and Thailand), one European (Turkey), six Latin American (Argentina, Brazil, Colombia, Mexico, Uruguay and Venezuela), two South Asian (India and Sri Lanka), and one African (Kenya).

Data processing and crisis period identification follow four steps:

- (i) Choose an indicator for each crisis type;

- (ii) Standardize indicators on a five years moving average basis;

- (iii) Compare standardized scores with the crisis threshold (-2.0);

(iv) Identify crisis periods if standardized scores exceed the threshold.

These four steps enable us to identify the periods experiencing crises. Crisis period identification is useful for detailed analysis of crises. However, at the same time, the crisis period identification captures spurious signals of the start and end of crises. Then after identifying crisis periods, crisis episodes, which are the core part of crises, are identified using two sets of conditions. The first condition is that there should be at least two types of crises in the same period to pinpoint the start of the crisis episodes. This condition is set to exclude spurious signals of the start of the crisis episodes. As such, all periods with more than two crisis types are included in crisis episodes. The second condition is window periods, and this article sets three quarters window periods based on existing crisis studies. When the period gap between two crisis episodes are less or equal to three quarters, these three quarters are also included in one crisis episode even if these periods has at most one crisis type. This condition is set to exclude spurious signals of the end of the crisis episodes.

Fig. 2 illustrates the relationship between crisis periods and crisis episodes with the symbol (? ) denote crisis periods. In period (A), only liquidity type banking crises are identified and therefore this period is not identified as the start of a crisis episode. On the other hand, period (C), period (G) and period (L) has more 10