Table 4.
Solid firms – firms with expected positive EBITDA
| Variable | Mean | Std. Dev | Min | Max | |
|---|---|---|---|---|---|
| Ordinary | EBITDA_B | 3282.73 | 4095.59 | 0.12 | 19,995.18 |
| SURVIVE_B | 100.00% | - | 1.00 | 1.00 | |
| LIFE_DAYS_B | |||||
| COVID | EBITDA_C | − 162.63 | 2654.39 | − 21,817.01 | 19,811.36 |
| SURVIVE_C | 54.97% | 0.50 | - | 1.00 | |
| LIFE_DAYS_C | 155 | 151 | - | 547 | |
| Gov’t Policies | EBITDA_G | 106.69 | 2516.90 | − 19,247.13 | 19,811.36 |
| SURVIVE_G | 65.35% | 0.48 | - | 1.00 | |
| LIFE_DAYS_G | 180 | 153 | - | 547 | |
| LIFE_DAYS_G + 25,000 | 188 | 151 | 1 | 547 | |
| LIFE_DAYS_G + 50,000 | 193 | 150 | 1 | 547 | |
| Effects of jobs | Job_loss_B | 0 | |||
| Job_loss_C | 14,382 | ||||
| Job_loss_G | 11,066 | ||||
This table presents the results for tree scenarios: ordinary scenario, impact of COVID-19 and government intervention policies; and their impact on the performance and residual life of the firm focusing only on the SMEs with expected positive EBITDA. The variables are defined as follows: EBITDA_B, estimate of the EBTDA under standard condition; SURVIVE_B, proportion of firms that have a positive estimated EBITDA; LIFE_DAYS_B, days of available cash to cover the negative EBITDA_B (the value is estimated only for those firms with a negative EBITDA_B; EBITDA_C, estimate of the EBTDA under COVID-1919 shock; SURVIVE_C, proportion of firms that have a positive estimated EBITDA under COVID-19; LIFE_DAYS_C, days of available cash to cover the negative EBITDA_C (the value is estimated only for those firms with a negative EBITDA_C); EBITDA_G, estimate of the EBTDA under including the effect of government mitigation policies; SURVIVE_G, proportion of firms that have a positive estimated EBITDA under government mitigation policies; LIFE_DAYS_C, days of available cash to cover the negative EBITDA_G (the value is estimated only for those firms with a negative EBITDA_G); JOB_LOSS_B, number of jobs at risk in the ordinary scenario (e.g. number of jobs linked to firms with a negative EBITDA_B); JOB_LOSS_G, number of jobs at risk in the COVID-19 scenario (e.g. number jobs linked to firms with a negative EBITDA_C); JOB_LOSS_G, number of jobs at risk in the scenario with mitigating policies (e.g. number jobs linked to firms with a negative EBITDA_G)
n 31,940