Algorithmic Pricing and Transparency in the Gig Economy

Funded Research Proposal

Algorithms control pricing and match customers and workers in the gig economy. However, algorithms face several critiques: they lack transparency, can be biased, and can be inefficient. We empirically analyze these issues and show that algorithms lose efficiency from two sources: competition between platforms and misaligned worker incentives. We model workers’ strategic responses to variation in pricing and estimate counterfactuals on the effects of minimum wage and transparent pricing policies.Read More

Creative Disruption? Innovations in Supply Chain Management

Executive Summary:  Our Spring ‘23 conference, “Creative Disruption? Innovations in Supply Chain Management,” highlighted the challenges and opportunities faced by global supply chains in the wake of unprecedented disruptions. Speakers from academia and industry discussed such themes as the balance between efficiency and resilience, the role of advanced technologies inRead 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