PhD scholar, IIT Delhi


I design, build and deploy IT tools which help in the empowerment of marginalised communities

Governments in developing countries (like India) design affirmative action programmes for the benefit of marginalised communities. For example, in India there is an employment guarantee programme, a food subsidy programme, health care programmes, etc. However, there are several gaps when it comes to the implementation of these programmes on the ground. The beneficiaries are often from poorly educated backgrounds and do not have access to the Internet. So they are not able to access the information published by the government. They are also not empowered enough to access the grievance redressal helplines run by the government, My solution is to use automated voice-based phone calls (Interactive Voice Response: IVR) to communicate the information on websites to the beneficiaries. My tool crawls the information on the websites (like wages paid to the workers), calls the beneficiary automatically to communicate the information (your account has been credited X amount), and verifies the information (press 1 to confirm the payment, press 2 to deny the payment). I was able to highlight several cases of wrong information through this process. I also set up a grievance redressal model mediated by empowered civil society volunteers. These volunteers are from the same community as the beneficiaries but are better educated and have connections in the local government offices and in the media. I set up an IVR (Interactive Voice Response) platform on which beneficiaries can file grievances on government schemes. The team of volunteers can access the grievances through the IVR or through an Android App (built for this purpose) and follow-up on the grievances through their connections. They could also record updates for the beneficiaries and connect with the beneficiaries for follow-up. This was deployed in 4 districts in rural India and we achieved a 70% redressal rate for the grievances which were taken up.


An analysis of the social impact of the stipend program for secondary school girls of Khyber Pakhtunkhwa

Abstract: The present study carries out an impact analysis of a conditional cash transfer (CCT) program for secondary-school girls in seven districts of Khyber Pakhtunkhwa province in Pakistan, including Battagram, Bonair, Hangu, Kohistan, Shangla, Tank, and Upper Dir. In 2012 we collected household-level primary data and used a probit model for quantitative analysis. Further, we conducted various focus group discussions and key informant interviews in the target areas. Results show that the chances of female schooling decrease with a rise in family size. The chances of female education increase by 1.8 and by 3.3 % if household heads and their spouses have one additional year of schooling, respectively. Better educational services and rises in family income increase the chances of female ecucation by 11 and 0.3 %, respectively. Finally, socioeconomic awareness, improved economic conditions, and CCTs increase the chances of female education by 5.2, 4.7, and 0.03 %, respectively. Overall, the stipend program (CCTs) shows a pareto improvement. Our results indicate that 35 % of girls will drop out in the absence of a stipend program. The present study recommends that to increase program effectiveness, local-level monitoring and program evaluation may be improved, delays in stipend payments to female students should be reduced, a grievance redressal mechanism for parents and guardians should be introduced, and clear synergies should be developed with other transfer programs.

Pub.: 22 Aug '13, Pinned: 29 Aug '17