13 tabulated in Dickey and Fuller (1981) - on the joint hypotheses of unit root with no drift and no trend. We cannot reject the null of unit root without drift and trend.

|_LS//Dependent_<br>_Variable is MEX_<br>_Sample: 6/15/90 - 7/12/96_<br>_Included observations: 318_|_DIS_|||
|---|---|---|---|
|Variable<br>Coefficient<br>Std.|Error|T-Statistic|Prob.|
|MEXDIS(-I) 1.251215<br>0.05|5527|22.53350|0.0000|
|MEXDIS(-2) -0.222751<br>0.08|8032|-2.530349|0.0119|
|MEXDIS(-3) -0.193206<br>0.08|7332|-2.212301|0.0277|
|MEXDIS(-4) 0.159970<br>0.05|4736|2.922590|0.0037|
|R-squared<br>0.964241|Mea|n dependent var|657.8306|
|Adjusted R-squared 0.963899|S.D.|dependent var|282.6279|
|S.E. of regression<br>53.69972|Akai|ke info criterion|<br>7.979314|
|Sum squared resid<br>905469.2|Schw|artz criterion|8.026636|
|Log likelihood<br>-1715.933|F-sta|tistic|2822.343|
|Durbin-Watson stat 1.969546|Prob(|F-statistic)|0.000000|

This model is, in our opinion, consistent with the nature of the variable we are studying: it would be difficult to argue that the stripped spread should have a drift and/or a trend. On the other hand, the finding of unit root is consistent with the hypothesis that there is a learning process underlying risk premium movements: we can think of a shock as new information accruing between one period and the following; based on the new information traders update their prior on the probability of default, and set the risk premium based on the posterior probability. So the new information affects permanently the risk premium and its mean value. This is a layman's explanation of a unit root. 14 14 While the evidence of one unit root - we tested also the possibility of more than one unit root using the procedure proposed by Dikey and Pantula (1987); the null of two unit root is rejected - is strong on the complete sample, we wanted to check if the December 1994 crises represent a structural break that can cause a bias in our estimate of the unit root. We divided the sample in two (4/06/90 to 12/16/94 and 12/23/94 to 7/12/96) and performed unit root test on the two sub-samples. For the first sub-period, using F tests as tabulated by Dikey and Fuller (1981), we could not reject (at the 5% confidence level) the null of one unit root with no drift and no trend. If we maintain our hypothesis of no drift and no time trend, there is strong evidence of unit root also for the second sub-period. However, we performed an F test on the joint hypothesis of unit root with no drift and no trend and we rejected it. An ADF with drift and trend leads to rejection of unit root at the 5% critical level - but to not rejection at the I% critical level .

In conclusion, the hypothesis of unit root is strong on the complete sample. On the two sub-samples it is less strong. But under the hypothesis of no drift and no trend, in both cases we could not reject (at the 5% critical value) the null of unit root.

To gain more information on the possibility of unit root, we constructed two dummy variables: one _(dl)_ takes value one after 12/16/94 and zero before that date; the other _(dp)_ takes value one for (the four observations of) the month of December 1994 and zero otherwise. We regress MEXDIS on four lags of itself and on _dl;_ in a second regression we regress MEXDIS on the same four lags and on _dp._ The idea is that, if the true model is a stationary process with a structural change in the mean after December 1994. _dl_ should be significant. But it is not. While, if the true model is non stationary and there is a one time extra-shock in a unit root process (a single _pulse_ in the dummy variable will have a permanent effect on the mean value of the sequence), _dp_ should be significant. In fact it is