Table A1.
Spouse prescription usage - Logistic regressions
|
Model 1 |
Model 2 |
Model 3 |
||||
|---|---|---|---|---|---|---|
| Spouse prescription usage, time t | Spouse prescription usage, time t+1 | Spouse prescription usage, time t+2 | ||||
| Both types, present year t | 1.927*** | (0.020) | 1.859*** | (0.020) | 1.840*** | (0.021) |
| Personal equity | 0.99999996430*** | (0.00000000266) | 0.99999996920*** | (0.00000000262) | 0.99999997730*** | (0.00000000249) |
| Job change | ||||||
| Group 1 (to unemployment) | 0.953** | (0.022) | 0.963 | (0.022) | 0.977 | (0.023) |
| Group 2 (to new job) | 0.887*** | (0.010) | 0.878*** | (0.010) | 0.869*** | (0.010) |
| Education | 1.001*** | (0.000) | 1.000*** | (0.000) | 1.000*** | (0.000) |
| Female | 0.949*** | (0.007) | 0.948*** | (0.007) | 0.938*** | (0.007) |
| Age | 1.049*** | (0.000) | 1.046*** | (0.000) | 1.043*** | (0.000) |
| Personal income | 1.00000003840*** | (0.00000000533) | 1.00000001366 | (0.00000000859) | 0.99999999983 | (0.00000000371) |
| Observations | 45,13,276 | 45,13,276 | 45,13,276 | |||
| Log likelihood | −448583.6 | −433818.7 | −417275.9 | |||
| Pseudo R-squared | 0.040 | 0.035 | 0.032 | |||
| Year fixed effects |
No |
No |
No |
|||
| Model 4 | Model 5 | Model 6 | ||||
| Spouse prescription usage, time t |
Spouse prescription usage, time t+1 |
Spouse prescription usage, time t+2 |
||||
| Both types, present year t | 1.920*** | (0.020) | 1.768*** | (0.020) | 1.707*** | (0.020) |
| Personal equity | 0.99999996170*** | (0.00000000272) | 0.99999994335*** | (0.00000000310) | 0.99999992538*** | (0.00000000348) |
| Job change | ||||||
| Group 1 (to unemployment) | 0.953** | (0.022) | 0.944** | (0.022) | 0.936*** | (0.022) |
| Group 2 (to new job) | 0.885*** | (0.010) | 0.880*** | (0.010) | 0.874*** | (0.010) |
| Education | 1.001*** | (0.000) | 1.001*** | (0.000) | 1.001*** | (0.000) |
| Female | 0.949*** | (0.007) | 0.950*** | (0.007) | 0.941*** | (0.007) |
| Age | 1.049*** | (0.000) | 1.048*** | (0.000) | 1.047*** | (0.000) |
| Personal income | 1.00000004095*** | (0.00000000539) | 1.00000006377*** | (0.00000000713) | 1.00000007566*** | (0.00000000734) |
| Observations | 45,13,276 | 41,82,607 | 38,57,295 | |||
| Log likelihood | −448377 | −425894.4 | −402161 | |||
| Pseudo R-squared | 0.040 | 0.038 | 0.036 | |||
| Year fixed effects | Yes | Yes | Yes | |||
Note: This table presents the odds ratios and standard errors of logistic regressions of predictors on spouse prescription usage in t, t+1, and t+2. Models 4, 5, and 6 include Year fixed effects. Odds ratios marked with ***, **, or * are significant at the p < 0.01, 0.05, or 0.10 level, respectively. Spouse prescription usage in t, t+1, t+2, are indicator variables taking the value of 1, if the spouse had at least one prescription in the respective year, and 0 otherwise. Both types, present year t is an indicator variable taking the value 1, if the focal person had at least one prescription in the given year, and 0 otherwise. Personal equity is the focal person's net worth (in DKK). Job change is a categorical variable with Group 1 taking the value of 1, if the focal person changes to unemployment and Group 2 taking the value of 2, if the focal person changes to a new job, and 0 otherwise. Education denotes the months of education of the focal person. Female is an indicator variable, taking the value of 1, if the focal person is female, and 0 otherwise. Age is the focal person's age (in years). Personal income is the focal person's income (in DKK).