**Table 2: Descriptive Statistics Before and After Weighting and Covariate Balancing**

||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|
|---|---|---|---|---|---|---|---|
||**A**<br>**GovTec**<br>**h**|**B**<br>**Without**<br>**-**<br>**GovTec**<br>**h**|**C=A-B**<br>**Difference**|**D**<br>**p_value**|**E=Weight*B**<br>**Webal***<br>**Without-**<br>**GovTech**|**F=A-E**<br>**Difference**|**G**<br>**p_value**|
|Democracy (Polity 2)|5.45|3.677|1.773|0.073|5.45|0|1.000|
|GDP per capita (ln)|9.841|8.815|1.026|0.000|9.841|0|1.000|
|Fixed broadband<br>subscriptions|21.07|8.51|12.56|0.000|21.07|0|1.000|
|Public sector<br>corruption|0.4688|0.7385|-0.2697|0.000|0.4688|0|1.000|
|Population 15 - 44|20.94|22.08|-1.14|0.003|20.94|0|1.000|
|Equal distribution of<br>political power|2.438|2.046|0.392|0.013|2.437|0.001|1.000|
|Human capital index|0.6249|0.4924|0.1325|0.000|0.6249|0|1.000|

**_Note:_** _This table presents the sample means of the covariates before weighting for the treated units in column (1) and the control group in column (2). Column (5) shows the synthetic control group obtained by balancing the entropy. Columns (3) - (4) and (6) - (7), respectively, show the mean difference and the p_value of the mean difference t-test before and after weighting._

As noted, this study estimates the causal effect of GovTech platforms on two forms of citizen engagement variables, namely, the V-Dem Civil Society Participation Index (CPSI) and the Engaged Society (ES) indicator using the weighted least squares estimator as a second step of the entropy balancing. The results of the estimations are presented in Table 3. Most of the estimations revealed a significant and positive impact of GovTech platforms on citizen engagement. The coefficient of the GovTech variable is not significant in only one baseline regression excluding the matching covariates. An omitted variable bias is to be expected in the baseline estimations. As such, the introduction of control variables could enhance the impact of GovTech platforms on civil engagement.

The results obtained through the multiple regressions that control for the covariates are positive at the 5 percent threshold regardless the form of civil engagement. These results are similar to those of Tolbert and Mossberger (2006) and Hofstra et al. (2023), who found that e-government can improve governments’ interactions with citizens and perceptions of responsiveness. As such, the adoption of digital platforms can: (i) help governments to reach a wider audience and foster meaningful participation of citizens/CSOs in the policy-making process by providing them with an accessible channel to engage with policy makers and participate in policy discussion and consultation while eliminating the geographical and environmental barriers; (ii) allow CSOs to provide real-time feedback to decision-makers and help to establish independent feedback mechanisms, ensuring that public deliberations are not influenced or biased by vested interests; and (iii) enable more people from diverse backgrounds to share their opinions, perspectives, concerns, and suggestions thus creating more inclusive and responsive governance systems at a reduced cost. The magnitude of the impact varies according to the form of citizen engagement. The estimated coefficient of the GovTech variable is 0.09 for the two estimations for which the study employed the civil society participation index as the dependent variable. CSPI captures the extent to which CSOs are consulted by policy makers and people (especially women) are involved in CSOs, and the process of nomination of the legislative candidates. The significantly positive coefficient of the GovTech variable is higher in the regression where the study used the engaged society indicator as the dependent variable 10