in the base year (2015) ( _φ_ in equation (2)). The brackets under the treatment effects are p-values from F-tests for significance of _β_ + _φ_ . Coefficients on the indicator variable for “no contract” suggest that individuals without a written contract in 2015 were less likely to participate in both health insurance and pensions. From the coefficient on the no-contracttreatment interaction term it is evident that for health insurance participation, the impact of the information intervention is significantly different for respondents with and without contracts in 2015. For those with contracts in the base year, there is no information intervention effect. Given that before the intervention 77% of our sample with written contracts already had health insurance, this should not be a surprise. The effect on those without contracts, though, is positive and statistically significant. On average the intervention increased health insurance participation for those previously without a contract by 3.2 percentage points, or a 23.2 percent increase over the 2015 participation rate of this group (which was 13.8%).

Participation in pensions, however, was not affected by the information intervention, regardless of whether the individual had a contract or not. This result was puzzling at first, and led us to explore heterogeneity in treatment effects with age of the recipient in a post hoc analyses: one explanation lies with the fact that a fairly large proportion of the sample was within 15 years of retirement age (18% of men and 15% of women) and could not enjoy the full benefits of pension participation. To examine this possibility, those individuals within fifteen years of the retirement age are excluded. For this restricted sample, the estimated results for the average treatment effects and heterogeneous effects are reported in Panel C of Table 2. Although the information intervention had a zero average effect for this group, the impact for those without a written contract is positive and statistically significant. In particular, for “young” individuals without a contract, the intervention increased pension participation by 3.9 percentage points, or a 25% increase in the participation rate of this group.

To understand the difference in treatment responses to pension participation of the “young” and “old” samples, we examined the wage responses to treatment for each group and show results in Table (3). To do this, we estimate models of ln(wage) in 2016 on the information treatment, 2015 ln(wage), and standard city fixed effects in model 1. Pre-treatment (2015) individual level controls (age, age-squared, gender, years of schooling, marital status and number of children) are included in model 2, and model 3 includes pre-treatment firm size and ownership indicator variables. With inclusion of the lagged ln(wage) term, the coefficient on the treatment may be interpreted as the contribution of the intervention to the increase (or decrease) in wages in the following period.<sup>17</sup> In the bare bones estimates (model 1) and models with a full set of pre-treatment controls (model 3), we find that older employees

> 17One might alternatively estimate this change by regressing the change in log wage on pre-treatment variables.

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