# **6 Discussion of experimental results**

## **6.1 Renewal success rates**

Table 3 presents the effects of information technology on the probability of successfully completing a renewal process. All the coefficients reported are marginal effects from probit regressions, and are separately estimated for male and female applicants to exploit the indigenous attire data collected for the subsample of female applicants.<sup>9</sup> The effect of information technology over traditional technology after controlling for renewal day fixed effects — that is, the coefficient _β_ in Equation 1 — is presented in columns (1) and (3) for male and female applicants, respectively. Columns (2) and (4) present instead the effect of information technology over traditional technology after controlling for police officer fixed effects — that is, the coefficient _γ_ in Equation 2. The estimation of these two regression models allows for assessing the extent to which unobserved police officer characteristics might be correlated with the ability to successfully complete a renewal process. Columns (5) to (8) show the results of estimating Equations 3 and 4, which control for the characteristics of the applicants and allow for technology to interact with these characteristics. Columns (5) and (6) show the estimates for the subsample of male applicants, while those for female applicants are reported in columns (7) and (8). These alternative specifications allow assessing the extent to which applicants’s characteristics might be important determinants of success rates across type of renewal process.

The results in Table 3 show that the adoption of information technology resulted in an overall improvement in the service provided by the Police within the process of renewing an ID card. Male applicants randomly assigned to the digital renewal process have on average between 11.55 and 13.22 percentage points higher probability of completing the process as compared to those randomly assigned to the manual one — 11.55 when controlling for renewal day fixed effects and 13.22 when controlling for police officer fixed effects. All of these effects are statistically significant at the 1 percent level. The estimates in columns (3) and (4) corroborate these findings for the subsample of female applicants. Female applicants randomly assigned to the digital renewal process have on average between 10.43 and 13.59 percentage points higher probability of completing the process as compared to those randomly assigned to the manual one — 13.59 when controlling for renewal day fixed effects and 10.43 when controlling for police officer fixed effects. All these effects are also statistically significant at the 1 percent.

The characteristics of applicants should not affect success rates. In practice, however, they might if police officers do not provide a homogeneous service across the population or if applicants are affected by bureaucracy differently based on their characteristics. Next, we explore the possibility that applicants’ characteristics might be important determinants of success rates. The results of this exercise are presented in columns (5) to (8) and interestingly present strong evidence that indeed success rates vary systematically across renewal process based on the characteristics of the applicants. Applicants from relatively disadvantaged backgrounds are much less likely to complete the renewal process. On average, applicants from rural areas are 10 percentage points less likely to complete the renewal process as compared to those from the urban

> 9Table A1-1 in the Appendix reports the results for the pooled sample, and shows that the sex of the applicant is not an important determinant of renewal outcomes.

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