platform adoption. Critical values vary from 1.16 to 1.95, suggesting that the results remain robust with respect to the conditional independence hypothesis.<sup>18</sup> The estimated effect of adopting GovTech platforms on citizen engagement ranges from 0.12 to 0.18 for the CSP and from 0.45 to 0.85 for engaged society, contingent upon the matching method and the year (2021 or 2022). This underscores that GovTech platform adoption contributes to an increase in citizen engagement. The Average Treatment Effects (ATE) are between 0.12 and 0.19 for CSP and between 0.54 and 0.76 for engaged society, signifying that GovTech platforms enhance citizen engagement for both adopters and non-adopters. These results are similar to the main results, confirming that the result is not sensitive to alternative matching methods.

**Table 6: The effects of GovTech platforms on civil engagement using PSM**<sup>**19**</sup>

|**Treatment variable: GovTech**|**1-nearest**<br>**neighbour**<br>**matching**|**2-nearest**<br>**neighbour**<br>**matching**|**3-nearest**<br>**neighbour**<br>**matching**|**Radius**<br>**caliper**<br>**matching**<br>|**Local Linear**<br>**matching**|**Kernel**<br>**matching**|
|---|---|---|---|---|---|---|
|<br>|<br> <br>*|<br>**Average Treat**<br>**|<br>**ment Effect o**<br>*|**(r=0.05)**<br>**f the Treated(**<br>*|**ATT)**<br>|*|
|Civil Society Participation 2021|0.1781|0.1672|0.1500|0.1161|0.1347|0.1205|
||(0.0906)|(0.0882)|(0.0770)|(0.0676)|(0.0936)|(0.0705)|
|Civil Society Participation 2022|0.2469**|0.2203**|0.1979**|0.1634**|0.1656|0.1683**|
||(0.1019)|(0.0892)|(0.0825)|(0.0812)|(0.1035)|(0.0795)|
|||**_Qu_**|**_ality of the M_**|**_atching_**|||
|Pseudo R2|0.041|0.019|0.016|0.009|0.041|0.009|
|Standardized bias (p-value)|0.242|0.760|0.823|0.966|0.242|0.955|
|Rosenbaum upper bound sensitivity test<br>(2021)|1.53|1.57|1.63|1.62|1.66|1.71|
|Rosenbaum upper bound sensitivity test<br>(2022)|1.58|1.83|1.95|1.80|1.85|1.92|
|Engaged society 2021|0.7250**|0.6500**|0.5292**|0.4502*|0.6304*|0.4706*|
||(0.3305)|(0.3097)|(0.2807)|(0.2853)|(0.3438)|(0.2618)|
|Engaged society 2022|0.8500**|0.7937**|0.7083***|0.6435**|0.7654**|0.6602**|
||(0.3462)|(0.3079)|(0.2913)|(0.2686)|(0.3282)|(0.2729)|
|||**_Qu_**|**_ality of the M_**|**_atching_**|||
|Pseudo R2|0.041|0.019|0.016|0.009|0.041|0.009|
|Standardized bias (p-value)|0.242|0.760|0.823|0.966|0.242|0.955|
|Rosenbaum upper bound sensitivity test<br>(2021)|1.16|1.23|1.29|1.23|1.27|1.29|
|Rosenbaum upper bound sensitivity test<br>(2022)|1.41|1.74|1.82|1.74|1.81|1.82|

Note: a) The Average Treatment Effect are 0.1212 (Civil Society Participation 2021); 0.1219 (Civil Society Participation 2022); 0.5404 (Engaged society 2021) and 0.7596 (Engaged society 2022) b) Standard errors in parentheses. ***significance level at 1 percent; **significance level at 5 percent; *significance level at 10 percent. Bootstrap replication=500. Observations/Treated=145/80

> 18 The test is performed at a level of 5%. It should be higher than 1, at least. Using the simulation-based sensitivity analysis presented by Ichino et al (2008), the robustness of the estimates is also tested in the event of a failure of the conditional independence hypothesis. The test suggests that any unobserved factor correlated with each of the covariates used in this study would not be sufficient to reduce the estimated mean treatment effect to zero.

> 19 The various values of Pseudo R2 and Standardized Bias (p-value) for each type of matching remain the same for both outputs across the two years. As for the ATE, its value does not differ according to the different types of matching, but rather according to the output.

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