Economics and finance

Professor Jeffery Zhang from Michigan Law will be speaking at our February blue bag lunch talk on Wednesday, February 1 at 12pm. The talk will be virtual on Zoom. Please register here by January 31. 

Professor Nejat Seyhun will discuss a new paper on "insider giving," as a potent substitute for insider trading due to lax reporting requirements and legal restrictions.

More than a decade after the 2008 financial crisis, U.S. policymakers still have not adequately addressed one of the primary causes of the crash: foreign banks.

The Data Privacy and Portability in Financial Technology Symposium celebrates the Michigan Technology Law Review’s 25th Anniversary by hosting an event dedicated to cutting-edge scholarship at the intersection of technology and the law. Specifically, this symposium is designed to examine the inherent tensions between securing privacy rights and the ease at which transactions occur, facilitated by new innovative technologies.

This will be a presentation of two large-scale field experiments designed to test the hypothesis that group membership can increase participation and pro-social lending for an online crowdlending community, Kiva. The first experiment uses variations on a simple email manipulation to encourage Kiva members to join a lending team, testing which types of team recommendation emails are most likely to get members to join teams as well as the subsequent impact on lending. We find that emails do increase the likelihood that a lender joins a team, and that joining a team increases lending in a short window following our intervention. The impact on lending is large relative to median lender lifetime loans. We also find that lenders are more likely to join teams recommended based on location similarity rather than team status. Our results suggest team recommendations can be an effective behavioral mechanism to increase pro-social lending. In a second field experiment, we manipulate forum messages to explore the underlying mechanisms for teams to be effective. 

Historically, public infrastructure systems such as roads, water utilities, and schools are financed using a combination of tax revenue, government and revenue-backed bonds. This system has repeatedly fallen short due to insufficient tax revenue and political aversion towards funding “social infrastructure”. Especially for schools, the access to quality infrastructure is highly correlated (in the US) to poverty, stemming from property values, credit worthiness and other factors. A recent bill (not passed) required a 1:6 leverage of federal with state and private finance, compared to 1:12 in Europe and 1:30 proposed under the Climate accords. Either infrastructure has not been built or upgraded, or private capital has stepped in the breach. At the Center for Smart Infrastructure Finance, we're asking whether data-driven models can close the gap by taking advantage of the internet of things (IoT): smart sensors that deliver information which can be monetized. This seminar will explore how private financing models that leverage digital data supply chains to attract 'efficient capital' (e.g. insurance, options trades, debt securities, variable interest rate bonds) can be adapted to financing public infrastructure while limiting recourse to the citizens that use it, and leveling the economic disparities of access.