Massive Online Open Courses (MOOCs) present the potential to deliver high quality education to a large number of students. But they suffer from low completion rates. This paper identifies disorganization as a factor behind failure to complete a MOOC. Students who enroll one day late are 17 percentage points less likely to earn a certificate than students who enroll exactly on time. This reflects selection, but it does seem to be related to demographic characteristics, motivation to complete the course, or ability. This suggests that building in even more structure in the MOOC could be a factor in improving performance.

January 2003

Economists have long been interested in the idea that there is a direct circular relation between poverty and low productivity, and not just one that is mediated by market failures, usually in asset markets. The nutrition-based efficiency wage model (Partha Dasgupta and Debraj Ray, 1987) is the canonical example of models where this happens: However it has been variously suggested (see for example T. N. Srinivasan, 1994) that the link from nutrition to productivity and especially the link from productivity to nutrition is too weak to be any more than a small part of the story. Partha Dasgupta himself acknowledges this when he writes nutrition-productivity construct provides a metaphor,..., for ... an economic environment harboring poverty traps (Partha Dasgupta, 1997, page 5). We propose an alternative approach to this question based on the idea that attention is a scarce resource that is important for productivity. Specifically, people may not be able to fully attend to their jobs if they are also worrying about problems at home and being distracted in this way reduces productivity. But not paying attention at home is also costly: early symptoms of a child's sickness may go unnoticed; water may run out at the end of the day; kerosene for lighting lamps at home might run out and make it hard to do homework; etc. Finally, the extent to which home life distracts depends on the nature of home life. Specifically, certain goods (e.g. a good baby sitter, a 24-hour piped water supply, a connection to a power supply grid) can reduce the extent of home life distraction. These three assumptions generate an interesting relation between income and productivity that is at the core of our model. The non-poor in this model, by virtue of owning distraction-saving goods and services at home, are able to focus more on their work. Hence they will be more productive at work and will be able to afford more distraction-saving goods. This simple two-way relationship between in(This abstract was borrowed from another version of this item.)

This paper studies the problem of experiment design by an ambiguity-averse decision-maker who trades off subjective expected performance against robust performance guarantees. This framework accounts for real-world experimenters’ preference for randomization. It also clarifies the circumstances in which randomization is optimal: when the available sample size is large and robustness is an important concern. We apply our model to shed light on the practice of rerandomization, used to improve balance across treatment and control groups. We show that rerandomization creates a trade-off between subjective performance and robust performance guarantees. However, robust performance guarantees diminish very slowly with the number of rerandomizations. This suggests that moderate levels of rerandomization usefully expand the set of acceptable compromises between subjective performance and robustness. Targeting a fixed quantile of balance is safer than targeting an absolute balance objective.