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Essays in Behavioral Economics.

Strulov-Shlain, Avner.

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Essays in Behavioral Economics.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Essays in Behavioral Economics./
Author:	Strulov-Shlain, Avner.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	121 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
Contained By:	Dissertations Abstracts International81-04B.
Subject:	Economics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13884991
ISBN:	9781085793896

Essays in Behavioral Economics.
Strulov-Shlain, Avner.

Essays in Behavioral Economics. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 121 p.

Source: Dissertations Abstracts International, Volume: 81-04, Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2019.

This item must not be sold to any third party vendors.

This dissertation studies empirically and theoretically how firms should and do respond to biased consumers. Specifically, I study the magnitude and implications of left-digit bias, the tendency of people to overweight left-most digits, on firms pricing behavior and profits. In the first chapter, I ask why do so many prices end with 99 cents? 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.In the second chapter, I ask to what extent do firms understand their consumers? When consumers are left-digit biased, demand is discontinuous at round numbers making them dominated prices. I present evidence that firms exploit left-digit bias in the long-run. They act as if they know this demand structure, using round numbers only for 1%-2% of posted prices. However, due to a slight reform in the set of admissible prices, supermarket chains in Israel fail to respond optimally - Round numbers post-reform account for 20% of prices, making pricing sub-optimal. After about a year firms re-optimize, and the shares of round numbers drop. Suggestive evidence show that having more spatial competitors is correlated with faster re-learning. Combining the well-understood bias, data, and reform, allows a unique window to look into firms sophistication level. I conclude that firms do respond to biases in the long-run, but do not have a model of these biases in mind and hence fail to respond in the short-run.

ISBN: 9781085793896Subjects--Topical Terms:

517137
Economics.

Essays in Behavioral Economics.
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500 $a Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
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520 $a This dissertation studies empirically and theoretically how firms should and do respond to biased consumers. Specifically, I study the magnitude and implications of left-digit bias, the tendency of people to overweight left-most digits, on firms pricing behavior and profits. In the first chapter, I ask why do so many prices end with 99 cents? 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.In the second chapter, I ask to what extent do firms understand their consumers? When consumers are left-digit biased, demand is discontinuous at round numbers making them dominated prices. I present evidence that firms exploit left-digit bias in the long-run. They act as if they know this demand structure, using round numbers only for 1%-2% of posted prices. However, due to a slight reform in the set of admissible prices, supermarket chains in Israel fail to respond optimally - Round numbers post-reform account for 20% of prices, making pricing sub-optimal. After about a year firms re-optimize, and the shares of round numbers drop. Suggestive evidence show that having more spatial competitors is correlated with faster re-learning. Combining the well-understood bias, data, and reform, allows a unique window to look into firms sophistication level. I conclude that firms do respond to biases in the long-run, but do not have a model of these biases in mind and hence fail to respond in the short-run.
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