otherwise. These two variables reflect individuals’ engagement with the survey, which should not be directly related to the decision to participate in insurance.

A respondent’s level of trust in the social insurance system and own trustworthiness may be positively correlated, and so one might worry that trustworthiness revealed in these answers could be correlated with whether an individual participates in the social insurance programs, rendering these variables problematic. To overcome this potential problem, the vector of individual controls, **X** 1 _ij_ , includes a self-assessed indicator of trust in some models to directly control for this potential channel through which the exclusion restriction would be violated.<sup>24</sup> As this question on trust was only answered by individuals who were present at the time of the 2015 survey, the sample with responses on trust is reduced by one-third.

We estimate the sample selection correction model for equations (2) and (3) using the Heckman two-step method and confidence intervals are estimated using a bootstrap with 1,000 replications. The selected results of the first stage estimation of equation (5) are reported in Online Appendix A.4. For the full sample estimation, the two instruments are jointly statistically significant with signs and magnitudes that are intuitively reasonable. Those who are regarded as serious about the survey and with answers to questions judged to be more reliable are also more likely to participate in the next survey round. The weak-IV F-tests for the two specifications are 14.36 and 14.18. For the smaller sample that includes the trust measure, the IVs are weaker with F-test statistics of 11.<sup>25</sup> The selected results for the sample selection correction model of equations (2) and (3) are reported in Table 6. The results reported in Panel A include the full sample without controlling for trust, Panel B uses the sample individuals with the trust measure and includes the trust variable among controls, while Panel C uses the trust sample and does not control for trust. The results in Panel A show that controlling for sample selection bias does not change our main results. The coefficient on the level of intention to treat controlling for city premium varying treatment effect is 10.6 percentage points as opposed to the 9.1 percentage points in the model not controlling for attrition bias. In addition, the sample selection correction term, _λ_ , is statistically insignificant. In the case of equation (2), the intention to treat effect for those without a contract in the base year is 3.7 (0.001-0.071) percentage points, instead of 3.2 percentage points when not controlling for attrition.

When we exclude individuals with missing trust variable (the sample size falls from 6,396 to 4,037 in the first step estimation and from 4,587 to 2,881 in the second step) and controlling

> 24The question on trust reads “In general, do you think majority of people can be trusted or one should be careful when dealing with people in general? 1. Majority of people can be trusted; 2. One should always be careful; 3. Do not know”. We define the ‘trust’ dummy variable as those who answer “1”.

> 25We also used instruments separately. While the IV in the trust sample passes the rule of thumb test for strong instrument, the F-test on reliableness IV is 6.9. The second stage results do not differ much from those reported below. These results are available upon request from the authors.

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