University of Maryland
Department of Economics
3114 Tydings Hall
College Park, MD 20742
Institutional Affiliation: Lehigh University
NBER Working Papers and Publications
|May 2014||Banning Foreign Pharmacies from Sponsored Search: The Online Consumer Response|
with Matthew Chesnes, Ginger Zhe Jin: w20088
Increased competition from the internet has raised concerns about the quality of prescription drugs sold online. Given the pressure from the Department of Justice, Google agreed to ban pharmacies not certified by the National Association of Boards of Pharmacy (NABP) from sponsored search listings. Using comScore click-through data originated from health-related queries, we study how the ban affects consumer search and click behavior in a difference-in-differences framework using the synthetic control method. We find that non-NABP-certified pharmacies receive fewer clicks after the ban and this effect is heterogeneous. In particular, pharmacies not certified by the NABP, but certified by other sources (other-certified websites), experience an increase in organic clicks that partially offset...
Published: Matthew Chesnes & Weijia (Daisy) Dai & Ginger Zhe Jin, 2017. "Banning Foreign Pharmacies from Sponsored Search: The Online Consumer Response," Marketing Science, vol 36(6), pages 879-907.
|November 2012||Aggregation of Consumer Ratings: An Application to Yelp.com|
with Ginger Z. Jin, Jungmin Lee, Michael Luca: w18567
Because consumer reviews leverage the wisdom of the crowd, the way in which they are aggregated is a central decision faced by platforms. We explore this "rating aggregation problem" and offer a structural approach to solving it, allowing for (1) reviewers to vary in stringency and accuracy, (2) reviewers to be influenced by existing reviews, and (3) product quality to change over time. Applying this to restaurant reviews from Yelp.com, we construct an adjusted average rating and show that even a simple algorithm can lead to large information efficiency gains relative to the arithmetic average.