I am a Behavioral Economist, focusing on questions in Quantitative Marketing, Industrial Organization, and Public Economics. I am interested in how humans make decisions and experience them, and their interactions with the other side of the market, such as firms, the government, and employers.
I obtained my PhD in Economics from the University of California, Berkeley.
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Revise and Resubmit The Review of Economic Studies
Firms arguably price at 99-ending prices because of left-digit bias, the tendency of consumers to perceive a $4.99 as much lower than $5.00. Using retail scanner data on thousands of products and dozens of retailers, I provide reduced-form support for this explanation. I then structurally estimate the magnitude of left-digit bias, and find that consumers respond to a 1-cent increase from a 99-ending price as if it were a 15-25 cent increase. Next, I analyze how firms should respond to left-digit biased demand. I solve and estimate a model that makes three key predictions: (1) prices should bunch at 99-ending prices; (2) there should be ranges of missing prices with low price-endings; (3) these ranges of missing prices should increase with the dollar digit. Qualitatively, these predictions hold. Firms respond to the bias with high shares of 99s and missing low-ending prices. Quantitatively, however, firms price as if the bias were much smaller and demand were more elastic, so they use dominated prices. I estimate that the retailer is forgoing 1-3 percents of potential gross profits due to this misperception.
Firm Sophistication: A Natural Experiment on Price Endings
I present evidence of firms learning and understanding of consumer biases. Firms exploit consumer biases to increase profits, but are not sophisticated about it in the sense that they do not seem to have a model of demand in mind. In particular, after a policy restricted what prices can be charged, it takes supermarket chains about a year of exploration to re-optimize. I exploit a policy change in Israel where the government banned pricing in non-existing coins, which banned firms from pricing in the modal price ending of .99. Under weak assumptions about the forces driving the .99 price ending to be prevalent to begin with, rounding the price to end with .00 is almost never optimal. However, firms initially set a high share of products to end with .00 and lose a few percentages of revenue in response. Over time, the share of .00s drops, following the model's predictions.