Table 1.
Calibration and estimation of model parameters: Rio de Janeiro.
Parameter | Value | Interpretation | Source |
---|---|---|---|
Panel A: City parameters (6 parameters) | |||
0.222 | Fraction of people living in slums | Census | |
1 | Wage rate of non-slum agents | Normalization | |
0.277 | Wage rate of slum agents | Census | |
0.065 | Frac. of space assigned to slums | Census | |
0.934 | Frac. of space assigned to areas wo slums | Census | |
0.334 | Prop. of time spent within group | Work/all time outside | |
Panel B: Disease parameters (15 parameters) | |||
11.43 | Infectiousness of Covid-19 | Internally estimated | |
, | 1 | Prob. (serious sympt. no recovery from mild) | 1 week w/mild symptoms |
0.971 | Prob. of recovery from mild Covid-19, other | CDC & Verity et al. (2020) | |
0.979 | Prob. of recovery from mild Covid-19, slum | CDC & Verity et al. (2020) | |
, | 0.284 | Prob. of recovery from serious Covid-19 | CDC & Verity et al. (2020) |
0.118 | Wkly death rate, other; critically ill with ICU | CDC & Verity et al. (2020) | |
0.073 | Wkly death rate, slum; critically ill with ICU | CDC & Verity et al. (2020) | |
, | 1.0 | Wkly death rate; critically ill wo ICU | Assumption |
0.158 | Infections through the health care system | Butler et al. (2018) | |
0.152 | Prop. non-slum agents with priv. insurance | ANS | |
8.12e−5 | ICU beds (per capita) in public system | Covid Radar | |
4.9e−4 | ICU beds (per capita) in private system | Covid Radar | |
Panel C: Preference parameters (7 parameters) | |||
−1.72 | Elast. of subst. bw leisure time and goods | Kopecky (2011) | |
0.108 | Production of leisure goods | Internally estimated | |
1.089 | Rel. utility weight—leisure goods | Internally estimated | |
2.453 | Rel. utility weight—leisure at home | Internally estimated | |
1.995 | Rel. utility weight—leisure at home; infected | Internally estimated | |
Discount factor | Standard | ||
8.575 | Value of being alive | Internally estimated |