Using Technology to Improve Direct Benefit Transfer in India
Can using technological innovations for monitoring and information sharing improve the implementation of social protection programs? In partnership with the Ministry of Rural Development, researchers are conducting a randomized evaluation of a new internet- and mobile-based management and monitoring platform, PayDash, to improve the administration of MGNREGA in India.
Increasingly, countries across the world use social protection programs to redistribute gains from economic growth and to protect poor households from downturns. Yet, programs often face challenges ensuring that intended recipients are targeted successfully and receive benefits in a timely fashion. State capacity is often inadequate to administer these programs effectively and without corruption, often to the detriment of the most vulnerable beneficiaries. In environments with corruption, government officials may be limited in their ability to monitor program implementation, such as being able to correctly identify the sources of payment delays and determine who to hold accountable. In such contexts, can technological innovations to share information help social protection programs reach their intended beneficiaries?
India is an important example of an emerging economy that has expanded its use of social protection programs but struggles with program implementation. The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is a key piece of India’s social protection system, which provides each rural household with up to one hundred days of annual unskilled labor employment. Between 2014 and 2015, 41 million rural households benefited from the program at a cost of approximately US $5.9 billion. Multiple studies document MGNREGA’s positive impact on rural households’ well-being.1 However, the program often suffers from payment delays, low participation, and other sources of leakages.
MGNREGA recently transitioned to electronic payment systems, following a larger move within the Government of India to transition social programs from in-kind cash payments to Direct Benefit Transfers (DBT). The new DBT system aims to reduce leakages in the program by ensuring that fund flows from central to local levels are based on incurred rather than planned expenditures. However, national averages suggest that the transition to electronic payment systems has been associated with higher payment delays. These payment delays could be a reason for reduced participation in MGNREGA by the poorest intended beneficiaries.
In partnership with the Ministry of Rural Development, researchers are conducting a randomized evaluation of a management and monitoring platform, PayDash, to improve the administration of MGNREGA. PayDash is a new internet- and mobile-based application for government officials. It tracks when each step in the payment process occurs and generates real-time information on delayed payments linked to information on employees responsible for each administrative step. While information relevant to payment delays is accessible through the MGNREGA website, PayDash presents this information in a more accessible and actionable format to government officials.
The evaluation will take place in 704 blocks (district sub-divisions) across 98 districts in three states, Madhya Pradesh, Chhattisgarh, and Jharkhand. Different levels of the bureaucratic hierarchy responsible for program administration will receive the platform. Districts will randomly be assigned to one of four groups:
- Receive PayDash at the block level
- Receive PayDash at the district level
- Receive PayDash at the block and district level
- A comparison group that does not receive PayDash
To measure the impact of PayDash on the timing and reliability of MGNREGA payments and program participation, researchers will use web application programming interfaces (APIs) and an internal monitoring dashboard to collect real-time data on PayDash usage and subsequent disciplinary actions taken by officers. Surveys with officers will provide information on whether officers’ personality traits, such as their intrinsic motivation or propensity for corruption, influence the intervention’s impacts.
Project ongoing; results forthcoming.
1Muralidharan, Karthik, Paul Niehaus, and Sandip Sukhtankar. “Building State Capacity: Evidence from Biometric Smartcards in India.” Working Paper, February 2016. and Banerjee, Abhijit, Esther Duflo, Clement Imbert, Santhosh Mathew, and Rohini Pande. “E-governance, Accountability, and Leakage in Public Programs: Experimental Evidence from a Financial Management Reform in India.” Working Paper, October 2016.