Table 2.
Determinants of catastrophic health expenditure
| Health expenditure | CHE10 | CHE25 | ||||
|---|---|---|---|---|---|---|
| 65 + y/o member in a household | 0.01** | 0.02** | 0.00 | |||
| (0.00) | (0.01) | (0.00) | ||||
| 75 + y/o member in a household | 0.01** | 0.02** | 0.01* | |||
| (0.00) | (0.01) | (0.00) | ||||
| Income | -0.00 | -0.00 | -0.01** | -0.01** | -0.00 | 0.00 |
| (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
| Savings | 0.00** | 0.00** | 0.00 | 0.00 | 0.00 | 0.00 |
| (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
| Household head being university graduate or higher | 0.00 | 0.00 | 0.01 | 0.01 | -0.00 | -0.00 |
| (0.00) | (0.00) | (0.01) | (0.01) | (0.01) | (0.01) | |
| Household head being in paid work | -0.01** | -0.01** | -0.04** | -0.04** | -0.02** | -0.02** |
| (0.00) | (0.00) | (0.01) | (0.01) | (0.00) | (0.00) | |
| House ownership | 0.01** | 0.01** | 0.03** | 0.03** | 0.01 | 0.01 |
| (0.00) | (0.00) | (0.01) | (0.01) | (0.00) | (0.00) | |
| Household size | 0.00# | 0.00# | -0.00 | -0.00 | 0.00 | 0.00 |
| (0.00) | (0.00) | (0.01) | (0.01) | (0.00) | (0.00) | |
| Individual-FE | Yes | Yes | Yes | Yes | Yes | Yes |
| City-by-Year-FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Constant | 0.05** | 0.05** | 0.16** | 0.16** | 0.02* | 0.02 |
| (0.01) | (0.01) | (0.03) | (0.03) | (0.01) | (0.01) | |
| Individuals | 7,898 | |||||
| Observations | 65,564 | |||||
Note: Health expenditure (% of total consumption) is transformed by the inverse hyperbolic sine transformation; CHE10 and CHE25 denote catastrophic health expenditure at 10% and 25% thresholds, respectively; Estimates by fixed-effects linear probability models; ** p < 0.01, * p < 0.05, # p < 0.10; Values are coefficients with cluster-robust standard errors in parentheses; Income and savings are equivalised by household size and transformed by the inverse hyperbolic sine transformation; Household size represents the log transformed number of household members; FE represents fixed-effects; Weighted by longitudinal weights to address for attrition bias; singleton observations are not used for estimations.