Table 4.
1 | 2 | 3 | |
---|---|---|---|
Total | Single | Multiple | |
Panel A: age 0–4 years | |||
Copayment abolition | |||
0.488*** | 0.985*** | −1.637*** | |
(0.230) | (0.242) | (0.254) | |
[62.91%] | [167.78%] | [−80.54%] | |
RD type | Sharp | Sharp | Sharp |
Panel B: age 5–64 years | |||
Copayment abolition | |||
0.272 | 0.681** | −0.927*** | |
(0.265) | (0.293) | (0.269) | |
[31.26%] | [97.59%] | [−60.43%] | |
RD type | Sharp | Fuzzy | Sharp |
Panel C: age 65+ years | |||
Copayment abolition | |||
0.437* | 0.491* | −0.437*** | |
(0.241) | (0.261) | (0.157) | |
[54.81%] | [63.39%] | [−35.40%] | |
RD type | Sharp | Fuzzy | Fuzzy |
Observations | 2688 | 2688 | 2688 |
Column 1 includes all outpatient visits. Columns 2 and 3 only include one-time visits and multiple visits, respectively. Covariate variables are included in the regression. A cluster–adjusted standard error is used to account for within-cluster correlation. We use a polynomial of order one and a triangular kernel function. A data-driven mean squared error optimal bandwidth selection is applied. *** Significant at the 1% level, ** Significant at the 5% level, * Significant at the 10% level.