We follow 822 applicants through the process of obtaining a driver's license in New Delhi, India. To understand how the bureaucracy responds to individual and social needs, participants were randomly assigned to one of three groups: bonus, lesson, and comparison groups. Participants in the bonus...

We study the allocation of driver's licenses in India by randomly assigning applicants to one of three groups: bonus (offered a bonus for obtaining a license quickly), lesson (offered free driving lessons), or comparison. Both the bonus and lesson groups are more likely to obtain licenses....

We follow 822 applicants through the process of obtaining a driver%u2019s license in New Delhi, India. To understand how the bureaucracy responds to individual and social needs, participants were randomly assigned to one of three groups: bonus, lesson, and comparison groups. Participants in the...

Many countries mandate affirmative action in university admissions for traditionally disadvantaged groups. Little is known about either the efficacy or costs of these programs. This paper examines affirmative action in engineering colleges in India for "lower-caste" groups. We find that it...

This paper examines an affirmative action program for "lower-caste" groups in engineering colleges in India. We study both the targeting properties of the program, and its implications for labor market outcomes. We find that affirmative action successfully targets the financially disadvantaged:...

In this paper, we provide a new framework for analyzing corruption in public bureaucracies. The standard way to model corruption is as an example of moral hazard, which then leads to a focus on better monitoring and stricter penalties with the eradication of corruption as the final goal. We...

Existing learning models attribute failures to learn to a lack of data. We model a different barrier. Given the large number of dimensions one could focus on when using a technology, people may fail to learn because they failed to notice important features of the data they possess. We conduct a...

Existing learning models attribute failures to learn to a lack of data. We model a different barrier. Given the large number of dimensions one could focus on when using a technology, people may fail to learn because they failed to notice important features of the data they possess. We conduct a...