UC Berkeley

This dissertation presents a three-part study in development economics. Each chapter investigates how technological innovations enable firms and individuals to overcome problems of asymmetric information - whether it be monitoring devices to help firms overcome problems of moral hazard; online job-boards to overcome search and matching frictions for job-seekers; or new agricultural techniques to increase information diffusion within social networks.

The first chapter examines the problem of moral hazard in employer--employee contracting and how this may be an important barrier to firm efficiency and growth in the developing world. To do so, we run an RCT with a fleet of 255 minibuses (matatus) in Nairobi, Kenya, where we introduce monitoring devices that track real-time vehicle location, daily productivity, and safety statistics. We randomize whether minibus owners have access to these monitoring data using a novel mobile app. This information allows owners in the treatment group to observe a more precise signal of driver effort, the amount of revenue drivers collected in fares, and the extent to which the driver engages in reckless driving. We find that treated vehicle owners modify the terms of the contract by decreasing the rental price they demand. Drivers respond by working more hours, decreasing behaviors that damage the vehicle, and under-reporting revenue by less. These changes improve firm profits and reduce management costs, thereby helping treated firms grow. The device also improves owners' trust in their drivers, which drivers say makes their job easier. Finally, we investigate whether these gains to the company come at the expense of passenger safety, in an environment where accidents are common. While we do not find any evidence that conditions deteriorate, offering detailed information on driving behavior also does not \emph{improve} safety. Only by incentivizing drivers through an additional cash treatment do we detect safety improvements.

The second chapter investigates how agents in a social network can be encouraged to obtain information from outside their peer groups. Using a field experiment in rural Bangladesh, we show that demonstration plots in agriculture --- a technique where the first users of a new variety cultivate it in a side-by-side comparison with an existing variety --- facilitate social learning by inducing conversations and information sharing outside of existing social networks. We compare these improvements in learning with those from seeding new technology with more central farmers in village social networks. The demonstration plots --- when cultivated by randomly selected farmers --- improve knowledge by just as much as seeding with more central farmers. Moreover, the demonstration plots only induce conversations and facilitate learning for farmers that were unconnected to entry points at baseline. Finally, we combine this diffusion experiment with an impact experiment to show that both demonstration plots and improved seeding transmit information to farmers that are less likely to benefit from the new innovation.

Finally, the third chapter explores the impact of online job platforms on labor market frictions in India. In recent years innovative job market information systems have emerged in order to match recent graduates with employers via integrated websites and call center based platforms. We use a randomized control trial to evaluate the ability of such job-portals to ease search frictions in India. We partner with Job Shikari, an online platform operating primarily in Northern India, and upload a randomly selected sample of recent vocational training graduates onto their platform. A second subset of graduates are uploaded to the platform, and receive ``priority status", which means they subsequently receive many more text messages than their peers about potentially job opportunities. We find that being uploaded to the job portal has a negative impact on the probability of being employed, but no significant impacts on job-search. The treatment priority group experiences a less strong disemployment effect, but is much more likely to respond to the treatment by migrating to urban centers. These results differ by job-seekers' observable characteristics such as age and martial status. We interpret our results as evidence that the impact of job-portals depends significantly on job-seekers beliefs about what the job-portal can do for them, rather than just on how well the platform can match the job-seeker with a particular job.