Duration of exclusion

Above we provided some information regarding the process of regaining access to credit after a default is cleared. In this subsection, we expand on the previous results by analyzing more aspects of the process. To start, we show non-parametric estimates of the survival and hazard functions of the time it takes for a rm to borrow again.⁶⁵ These results refer to the two denitions of access discussed previously, that is, the ability to borrow more money than before (strict denition) and the ability to keep having some loans (broad denition). Figures 4.4 and 4.5 refer to the former, while Figures 4.6 and 4.7

65The survival function is dened as the probability of regaining access to credit until w:

V(w) = Pr(W  w) = 1  I (w). The hazard function is dened as the probability of a rm leaving the exclusion state in the time interval [w> w + gw), conditional on being excluded from credit markets after the default is cleared: k(w) = limPr(wW w+gw|W w)

gw > gw $ 0. W denotes the time a rm remains excluded from access to credit after default.

refer to the latter.

Figure 4.4: Hazard function for time until more access

Note: Analysis time defined as quarters since the end of the first default episode. The hazard function is defined as the probability of regaining access to credit in the time interval [t, t+dt), conditional on not being in default: h(t) = lim Prob(t<=T<t+dt

| T>=t)/dt, as dt->0. More access is defined as having a larger amount of outstanding bank loans (including credit lines) than at the end of the default episode and not having any record of default or write-offs.

As seen in these gures, the two denitions are substantially dierent: while in one case around 60% of rms never regain access again (the strict denition of access), in the other case this gure is substantially lower (slightly less than 25%). Despite the dierences that are found in the right tails of the survival

Figure 4.5: Time until more access

Note: Analysis time defined as quarters since the end of the first default episode. The survivor estimate is defined as the probability of regaining access after default at t:

S(t)=Prob(T>=t)=1 - F(t). More access is defined as having a larger amount of outstanding bank loans (including credit lines) than at the end of the default episode and not having any record of default or write-offs.

0.000.250.500.751.00

0 20 40 60

analysis time Kaplan-Meier survival estimate

Figure 4.6: Hazard function for time until access

Note: Analysis time defined as quarters since the end of the first default episode. The hazard function is defined as the probability of regaining access to credit in the time interval [t, t+dt), conditional on not being in default: h(t) = lim Prob(t<=T<t+dt

| T>=t)/dt, as dt->0. Access is defined as having a positive amount of outstanding bank loans (including credit lines) without any record of default or write-offs, after having left default.

-0.10 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70

1 11 21 31 41 51

A na lysis time

Figure 4.7: Time until access

Note: Analysis time defined as quarters since the end of the first default episode. The survivor estimate is defined as the probability of regaining access after default at t:

S(t)=Prob(T>=t)=1 - F(t). Access is defined as having a positive amount of outstanding bank loans (including credit lines) without any record of default or write-offs, after having left default.

0.000.250.500.751.00

0 20 40 60

analysis time Kaplan-Meier survival estimate

functions, when we compare the two hazard functions we see that their shapes are very similar. In particular, we see that the rst 4 to 6 quarters after exiting default are fundamental for determining the ability to regain access to bank credit. When a rm is not able to regain access during this period, the probability of regaining access at any given time becomes very low (almost 0%).

In Table 4.5 we look at dierent snapshots of the distribution of possible outcomes after default in dierent moments in time, namely, 1 quarter, 2 quarters, and 1, 2 and 3 years after the rst default episode of each rm ends.

We consider the same set of outcomes depicted in Table 4.4.

Ta bl e 4 . 5 - Di stri buti o ns o ver ti m e o f po ssi bl e o utco m es a fter l ea vi ng defa ul t

1 quarter 10,552 12.8 38,022 46.1 7,355 8.9 11,252 13.6 - - 15,298 18.5 82,479

6 months 9,074 11.4 27,435 34.6 4,994 6.3 10,100 12.7 13,003 16.4 14,792 18.6 79,398 1 year 8,292 11.1 20,314 27.2 3,575 4.8 9,069 12.1 17,914 23.9 15,647 20.9 74,811 2 years 7,172 10.9 14,310 21.7 2,116 3.2 7,953 12.1 16,343 24.8 18,057 27.4 65,951 3 years 6,398 11.0 10,799 18.6 1,777 3.1 6,985 12.0 13,245 22.8 18,805 32.4 58,009

Notes: This table depicts snapshots of the distribution of possible outcomes after default in different moments in time (namely, 1 quarter, 2 quarters and 1, 2 and 3 years after default ends). A default episode is considered resolved if there is no record of loans with late repayments or in litigation in the end of the following quarter. We exclude firms that were in default in 2008Q4, the last quarter in the sample, and consider only the first default episode of each firm during the sample period. After default, firms can either continue to be observed in the credit register (columns 1-10) or they can cease to appear in the CRC (columns 11-12). In the latter case firms can have either ceased to operate or they can still be in operation but without having access to loans from financial institutions. By construction, there are no firms in default in the quarter after the default episode ended. Firms with more access are those with more outstanding bank loans (including credit lines) than at the end of the default episode and without any record of default or write-offs.

Firms with less access than before are those which have the same or less loans outstanding that at the end of the default episode.

Regarding the rms that continue to be observed in the CRC database after default, several things happen. First, we see that the percentage of rms with more access and without problem loans is relatively stable over time (column 2). At the same time, the percentage of rms with access to credit, but less than before, decreases substantially as time goes by — it goes from 46% to 19% in 3 years (column 4). This large variation seems to be directly related

to recidivism, as after 6 months around 16% of rms are in default again and after 1 year this value is around 24% (column 10). If we add columns (4) and (10) we see that the sum of the two is relatively stable over time. This suggests that a strong indicator of recidivism may be the inability to borrow more than before. Regarding the other possible outcomes, rms with access but still with some written-o loans (columns 5 and 6) and rms only with written-o loans but no access (columns 7 and 8), we observe that over time the number of

rms with access and with written o loans decreases substantially while the number of rms without access and with written-o loans does not change much. Finally, with respect to the rms that are not observed in the CRC, we see that this percentage is relatively stable in the rst year, but after 2 and 3 years it increases substantially — from around 18% to 30%. This possibly re ects the relatively short life span of micro and small rms, which comprise the bulk of our sample.⁶⁶