Table 2.
Estimation results: Marginal effects from probit estimation with positive attitude towards different technologies as dichotomous depentent variable
| Communication & entertainment | Support & health | |||
|---|---|---|---|---|
| Men | Women | Men | Women | |
| Age group (ref.: 50–59) | ||||
| 60–69 | 0.06 | 0.05 | 0.06 | 0.07 |
| (0.04) | (0.05) | (0.06) | (0.04) | |
| 70–79 | 0.25*** | 0.28*** | 0.05 | 0.07 |
| (0.05) | (0.06) | (0.06) | (0.04) | |
| 80+ | 0.47*** | 0.48*** | 0.01 | 0.05 |
| (0.07) | (0.07) | (0.07) | (0.05) | |
| Higher education (ref.: no) | ||||
| Yes | 0.18*** | 0.18*** | 0.11** | 0.06 |
| (0.04) | (0.05) | (0.04) | (0.03) | |
| Employment (ref.: retired/not employed) | ||||
| White collar | 0.13* | 0.18** | 0.15** | 0.04 |
| (0.05) | (0.06) | (0.05) | (0.06) | |
| Blue collar | 0.01 | 0.02 | 0.17** | 0.06 |
| (0.09) | (0.12) | (0.06) | (0.06) | |
| Financial distress (ref.: no) | ||||
| Yes | 0.01 | 0.06 | 0.06 | 0.02 |
| (0.05) | (0.04) | (0.05) | (0.03) | |
| Living in a house (ref.: no) | ||||
| Yes | 0.01 | 0.04 | 0.08 | 0.04 |
| (0.04) | (0.04) | (0.04) | (0.03) | |
| Urban area (ref.: no) | ||||
| Yes | 0.09* | 0.03 | 0.02 | 0.02 |
| (0.04) | (0.04) | (0.04) | (0.03) | |
| Partner in household (ref.: no) | ||||
| Yes | 0.01 | 0.02 | 0.04 | 0.02 |
| (0.04) | (0.03) | (0.04) | (0.03) | |
| Has children (ref.: no) | ||||
| Yes | 0.07 | 0.02 | 0.04 | 0.01 |
| (0.05) | (0.05) | (0.05) | (0.04) | |
| Poor or fair health (ref.: no) | ||||
| Yes | 0.05 | 0.03 | 0.17*** | 0.06* |
| (0.04) | (0.03) | (0.04) | (0.03) | |
| # IADL limitations | 0.01 | 0.06*** | 0.01 | 0.00 |
| (0.01) | (0.02) | (0.01) | (0.01) | |
| Observations | 1034 | 1372 | 1050 | 1461 |
Standard errors in parentheses. Marginal effects at means from probit estimation. +, *, **, ***