Table 3.
Weak firms – firms with expected negative EBITDA
| Variable | Mean | Std. Dev | Min | Max | |
|---|---|---|---|---|---|
| Ordinary | EBITDA_B | − 2852.23 | 3451.38 | − 19,990.02 | − 0.01 |
| SURVIVE_B | 0.00% | - | - | - | |
| LIFE_DAYS_B | 164 | 151 | - | 547 | |
| COVID-19 | EBITDA_C | − 3751.51 | 3961.70 | − 24,907.47 | - |
| SURVIVE_C | 0.00% | - | - | - | |
| LIFE_DAYS_C | 119 | 132 | - | 547 | |
| Gov’t mitigation policies | EBITDA_G | − 2845.14 | 3566.87 | − 19,997.38 | 16,184.65 |
| SURVIVE_G | 8.38% | 0.28 | - | 1.00 | |
| LIFE_DAYS_G | 186 | 151 | - | 547 | |
| LIFE_DAYS_G + 25,000 | 191 | 149 | 0 | 547 | |
| LIFE_DAYS_G + 50,000 | 194 | 148 | 1 | 547 | |
| Effects on jobs | Job_loss_B | 10,461 | |||
| Job_loss_C | 10,461 | ||||
| Job_loss_G | 9,584 |
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 negative 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 10,461