The Impact of Economic and Behavioral Drivers on Gig Economy Workers

Funded Research Proposal

In today’s ever-expanding “gig economy”, independent workers can freely choose when to work as well as seamlessly switch between multiple platforms that offer different incentives. Once a small minority of low-skilled workers with relatively low income, the gig economy now attracts high-skilled workers who are opting to join a flexible workforce. Read More

Optimizing Service using High Dimensional Panel Data

Funded Research Proposal

We study how retail stores’ multi-dimensioned service levels affect consumers’ buying behavior in a spatial setting. To this end, we propose the Double Block-Lasso BLP estimator, which combines the double selection procedure introduced in Belloni, Chernozhukov, and Hansen (2014), with demand estimation methods set forth in Berry, Levinsohn and Pakes (1995).Read More