Double Decoys and a Possible Parameterization: Empirical Analyses of Pairwise Normalization

11 Pages Posted: 17 May 2019

See all articles by Remi Daviet

Remi Daviet

University of Pennsylvania - Marketing Department

Ryan Webb

University of Toronto

Date Written: April 15, 2019

Abstract

In this article, we bring the pairwise normalization model to a stochastic setting. Our aim is two-fold. First, we examine novel predictions of the pairwise normalization model when multiple decoys are introduced into the choice set. We contrast these predictions with models which hypothesize that the range of attributes influences choice and conduct an experimental analysis to test for the presence of a “double decoy” effect. Second, we offer a parameterization of the pairwise normalization model for empirical settings. This extension includes weights on attribute dimensions to address subjective preferences and/or unit definitions, and allows for hypothesis testing for the presence of normalization in a choice dataset. We then analyze the pairwise normalization model on data from a choice experiment and find it outperforms the Logit model.

JEL Classification: D87

Suggested Citation

Daviet, Remi and Webb, Ryan, Double Decoys and a Possible Parameterization: Empirical Analyses of Pairwise Normalization (April 15, 2019). Available at SSRN: https://ssrn.com/abstract=3374514 or http://dx.doi.org/10.2139/ssrn.3374514

Remi Daviet

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States

Ryan Webb (Contact Author)

University of Toronto ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada

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