The good, the bad, and the ugly: An inquiry into the causes and nature of credit cycles
This paper builds models of nonlinear dynamics in the aggregate investment and borrower net worth to study the causes and nature of endogenous credit cycles. The basic model has two types of projects: the Good and the Bad. The Good projects rely on the inputs supplied by others who could undertake investment in the future, thereby improving their net worth. The Bad projects are independently profitable so that they do not improve the net worth of other borrowers. Furthermore, they are subject to the borrowing constraint due to some agency problems. With a low net worth, the agents cannot finance the Bad, and much of the credit goes to finance the Good, even when the Bad projects are more profitable than the Good projects. This over-investment to the Good creates a boom, leading to an improvement in borrower net worth. This makes it possible for the agents to finance the Bad. This shift in the composition of the credit from the Good to the Bad at the peak of the boom causes a deterioration of borrower net worth. The whole process repeats itself. Endogenous fluctuations occur, as the Good breed the Bad and the Bad destroy the Good. The model is then extended to add a third type of projects, the Ugly, which are unproductive but subject to no borrowing constraint. With a low net worth, the Good compete with the Ugly, which act as a drag on the Good, creating the credit multiplier effect. With a high net worth, the Good compete with the Bad, which destroy the Good, creating the credit reversal effect. By combining these two effects, this hybrid model generates intermittency phenomena, i.e., relatively long periods of small and persistent movements punctuated intermittently by seemingly random-looking behaviors. Along these cycles, the economy exhibits asymmetric fluctuations; it experiences a slow process of recovery from a recession, followed by a rapid expansion, and possibly after a period of high volatility, plunges into a recession.
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