experience the event would behave differently in the future than an individual who experienced the event". [Heckman, 1981, p91] In the context of sovereign default to the IBRD, structural state dependence would occur if a country which had previously defaulted would default again when faced with the exact same economic and political conditions under which a country that had not previously defaulted would not default. This might be the case if the experience of having defaulted once changes the way a country views subsequent default to the IBRD, perhaps as previous default has a permanent influence on creditworthiness reputation. In contrast _spurious state dependence_ occurs when "individuals differ in certain unmeasured variables that influence their probability of experiencing the event, but that are not influenced by the experience of the event. If these variables are correlated over time, and are not properly controlled, previous experience may appear to be a determinant of future experience solely because it is a proxy for such temporally persistent unobservables". [p91-92] The omission of political considerations in many previous studies would be one such occurrence.

These considerations mean that it is important to test for true versus spurious state dependence in order to determine whether a dynamic model is appropriate. Testing is complicated by the possible presence of heterogeneity, represented by the oi terms. Even if there is no state dependence, as long as there are individual effects in the model it will be the case that Pr(yitJxit,yitq)•Pr(yitIxit). Baltagi (1996) suggests that one first run the pooled logit model, and test whether y=O in the model Pr(y1t=l Ixit, **yit.J)** = F(xit'P+yyit.), where F(.) is the cdf of a logistic distribution. If the null hypothesis that y=O is not rejected, then we can proceed with the pooled logit model and ignore the panel nature of the data. Rejection of the null may occur due to serial correlation in the error term arising from individual effects, or from state dependence. Hsiao (1982) then outlines a simple test for state dependence, due to Chamberlain, which is based on whether or not there is a dynamic response to an intervention. After conditioning on the individual effects, as's, one includes lagged x's without lagged y's in the model, and tests the null of no state dependence by testing whether: Pr(yij=lJxit, xit .,...,ai)=Pr(yit=llxit,cxi). Rejection of the null indicates that there is state dependence, and hence the need to include lags of the dependent variable in the model.

The distinction between spurious and true state dependence is not just a question of econometric niceties. In their literature survey Aylward and Thorne (1998, p<sup>1</sup> 4) find that "past repayment history has been found to be significant in every study in which it has been tested". It is important to test, therefore, whether this merely reflects the omission of important variables from all such studies, or whether countries default behaviour does in fact change once it enters nonaccrual status.

# 5.4. **Measures of Fit**

Several measures are often used in the literature to evaluate the fit of binary choice models. One measure often reported is the pseudo-R<sup>2</sup> , given by the formula: 18