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Trade Finance in the Recovery of Trade Relations after Banking Crises
Figure 12.3 Recovery of Trade Relations, by Size
Kaplan-Meier survival estimates, percent
100
75
50
25
0 0
5
10
15
years exports at exit q1
exports at exit q2
exports at exit q3
Source: Authors’ calculations based on recovery dataset. Note: q = quantile. In the graph, higher survival rates imply longer periods of inactivity, therefore a lower probability of reentry. From the graph, it might seem that the variable size is not constant across time. This is controlled for in the regressions by stratifying the sample (see annex 12.1).
A possible intuition for this result is as follows: relationships with multiple spells before the crisis might be low-productivity ones, with productivity levels close to the cutoff that makes exporting profitable. These trade flows will therefore tend to reenter later than single-spell flows after a banking crisis. The previous regressions have been replicated, with the inclusion of a set of variables that capture sectoral financial dependence (table 12.6). The regressions do not show that the indicators of financial dependence have a significant effect. Table 12.7 presents an examination of whether such variables, despite not being significant per se, have an experience-specific effect. To do this, the Cox proportional model has been reestimated separately for each of the three groups of export experience. Reading across columns, it is possible to observe that the coefficients of both long-term EFD and trade credit dependence (TCD) change across quantiles, implying that there is indeed an experience-specific effect. Specifically, although for least-experienced products financial dependence has a negative impact on the