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Can we think of time variation in the frequency of corporate defaults as controlled by ’exogenous’ factors with no feedback from actual defaults to these factors? Or can we statistically document ’contagion effects’ by which one firm’s default increases the likelihood of other firms defaulting?
In a recent paper Das, Duffie, Kapadia, and Saita (2007) (DDKS) test whether default events in an intensity-based setting can reasonably be modeled as ’doubly stochastic’, i.e. as dependent solely on ’exogenous’ factors. Their approach is to transform the time scale using the sum of the default intensities estimated for individual firms and then test whether defaults on this transformed time scale behave as a standard Poisson process. Based on a time series of U.S. corporate defaults, they strongly reject that defaults can be modeled as doubly stochastic. DDKS view this test as a joint test of the specification of the default intensities of the individual firms and the doubly stochastic assumption. A core message of our paper is that the time transformation test should be thought of mainly as a misspecification test. We need - and propose - other tests to look for contagion effects that violate the doubly stochastic assumption.
The implications, for the efficiency of financial markets, of laws and regulations that protect creditors have been amply debated in the literature. Several authors have argued that protecting creditors has important benefits since it allows credit markets to provide funds at a low cost. When creditor rights are protected bylaw, outside investors are willing to pay more for financial assets-as equity and debt. Legal protection assures that more of firms profits would comeback to investors as interest or dividends.
