Table 2.
Predictors by business characteristics (N = 463).
| (1) |
(2) |
|
|---|---|---|
| Businesses experiencing income loss due to COVID-19 shock | Business reporting time to recover from COVID-19 shock to be more than a month | |
| Service sector | 0.075 (0.054) | 0.039 (0.038) |
| Manufacturing sector | −0.036 (0.055) | 0.067 (0.042) |
| Direct-to-consumer | −0.096* (0.050) | −0.017 (0.039) |
| Sole proprietorship | −0.036 (0.044) | −0.029 (0.033) |
| Cash flow problems during COVID-19 | 0.200*** (0.043) | 0.429*** (0.049) |
| Zero to 5 employees | 0.030 (0.047) | −0.136*** (0.035) |
| Family business | 0.047 (0.044) | 0.052 (0.033) |
| Operated from home | 0.104** (0.044) | −0.057 (0.036) |
| Number of years operating | 0.001 (0.001) | 0.001 (0.001) |
| Number of days closed COVID-19 | 0.003*** (0.00) | 0.001*** (0.00) |
| Female-owned business | 0.047 (0.043) | 0.013 (0.034) |
| Rural | −0.063 (0.055) | 0.003 (0.001) |
Linear probability model estimates are shown in both the columns. The coefficients reported are probabilities. Standard errors in parentheses are corrected for heteroskedasticity. *, **, ****p < 0.01, 0.05, 0.001. The estimates in both columns are results of a linear probability model. The regression includes business owner characteristics such as race, age, marital status, education, and region of residence.