Macroeconomic stability and banking soundness are inexorably linked. The instability in the macro-economy is associated with the instability in banking and financial markets and the instability in these sectors is associated with the instability in the macro-economy. On a survey of 53 industrial and developing countries conducted in 1998, the International Monetary Fund (IMF) identified 54 banking crises between 1975 and 1997. These crises were accompanied by downturns (recessions) in the macro-economy of 82 percent of sample, slightly more often in emerging economies than in industrial economies. The empirical evidence for most countries suggests that the instability generally starts in the macro-economy and spills over into the banking sector. The resulting banking sector instability, in turn, feeds back and aggravates the macro instability.

In order to reduce the risk of possible banking instability, it is necessary to identify the pattern of macroeconomic instability. The identification could be based on the macroeconomic shocks which can be caused by high inflation, deterioration in terms of trade, the sudden reversal of capital flows, etc. The identification is generally more forward looking. It is intended to determine the potential shocks that might take place in the particular economy.

The identification of macroeconomic shocks can be performed using the framework of business cycle analysis. The analysis provides a comprehension that macroeconomic random shocks are recurrent in different phases, although the shocks do not seem to follow a periodic pattern. Moreover, the analysis can detect the cyclical turning-points and the direction of economic activity. A timely understanding of the direction of economic activity is essential for the formulation of economic policies.

The business cycle analysis develops indicators that can reflect the movement of the cycle, which consists of lagging, coincident, and leading indicators. Each indicator has its own role to play in the analysis. The leading indicators are used to predict turning points in the economy. The coincident indicators are used to indicate the existence of turning point, while the lagging indicators are used to confirm the existence of turning point.

The business cycle analysis has two main benefits in predicting the crisis on the economy. First, early detection and timely recognition of business cycle turning points is important as it would allow policymakers to take preemptive policy measures. Second, it has long been recognized that business cycle analysis produces the indicators which are appropriate for turning point predictions that involve detecting regime shifts.

DEFINIT is appointed by the Indonesia Deposit Insurance Corporation (Lembaga Penjamin Simpanan/LPS) to construct Business Cycle Model based on best practices, robust empirical methodology, and adjusted to the LPS’s needs and preferences. The model also will formulate indicators that can be used for monitoring and predicting macroeconomic conditions. The model is expected to be a powerful tool for LPS to formulate policy in order to support LPS in carrying out its function, as one of the institutions that plays an active role in maintaining the stability of Indonesia’s financial system.