This grant funds three projects by the University of Chicago’s Macro-Financial Modeling (MFM) initiative. Led by University of Chicago economist and Nobel laureate Lars Peter Hansen and Andrew Lo of MIT, the MFM initiative is a group of distinguished economists, business professors, and other finance experts who have come together to meet the challenges of modeling the complex interactions between the real economy and modern financial institutions. The first supported project is a summer school for graduate students, which will bring young scholars from a variety of intellectual backgrounds to the University of Chicago to introduce them to macro-finanical modeling and to work on specific projects related to it. The second is an open call competition for new or crowd-sourced solutions to problems posed by the MFM initiative. The call will elicit the best thinking from outside the group, encourage innovative and creative approaches to established problems, and expand the reach of the initiative to those not yet involved in the program.  The third project is the development and construction of an online platform for comparing and archiving various macro-financial models. This platform will allow MFM scholars to compare, contrast, and evaluate different models and will spur integrative work that may lead to the combination or improvement of existing models.

The New York City Department of Health and Mental Hygiene (DOHMH) estimates that more than 1,000 restaurant-associated outbreaks of foodborne illness occur in the city each year. Outbreaks are usually reported by the victims themselves via telephone calls to 311 or the health department. Most victims don’t bother, however, and as a result the DOHMH detects only about 30 outbreaks each year. Since quickly detecting foodborne illness outbreaks is critical to implementing control measures in time to protect the public, better detection measures are needed. This grant funds a project by the Fund for the City of New York, in collaboration with the DOHMH and researchers at Columbia University to experiment with using Twitter and other social media to detect unreported instances of restaurant-related foodborne illness. The theory is that while people may be unlikely to report a foodborne illness to the health department, they are much more likely to tweet or post to Facebook about it. Real-time analysis of public data from Twitter and other social media sites may be able to reliably inform health department officials of outbreaks as they are happening. Over the next three years, the FCNY team will develop algorithmic methods for searching Twitter feeds, identifying tweets potentially relevant to foodborne illness outbreaks in NYC, and then evaluate the reliability of those algorithms in detecting actual outbreaks. Additional grant funds support efforts to increase voluntary reports of foodborne illness outbreaks by allowing NYC residents to report illness directly through Twitter. The project is experimental, but the prospective gains are large. Even a small increase in the ability to detect restaurant-related foodborne illness outbreaks would represent a significant improvement of current detection capabilities.