Supervised Machine Learning for Eliciting Individual Demand

69 Pages Posted: 13 May 2019 Last revised: 5 Feb 2021

See all articles by John A. Clithero

John A. Clithero

Lundquist College of Business, University of Oregon

Jae Joon Lee

Claremont Colleges - Claremont Graduate University

Joshua Tasoff

Claremont Colleges - Claremont Graduate University

Date Written: February 1, 2021

Abstract

Direct elicitation, guided by theory, is the standard method for eliciting latent preferences. The canonical direct-elicitation approach for measuring individuals' valuations for goods is the Becker-DeGroot-Marschak procedure, which generates willingness-to-pay (WTP) values that are imprecise and systematically biased by understating valuations. We show that enhancing elicited WTP values with supervised machine learning (SML) can substantially improve estimates of peoples' out-of-sample purchase behavior. Furthermore, swapping WTP data with choice data generated from a simple task, two-alternative forced choice, leads to comparable performance. Combining all the data with the best-performing SML methods yields large improvements in predicting out-of-sample purchases. We quantify the benefit of using various SML methods in conjunction with using different types of data. Our results suggest that prices set by SML would increase revenue by 28% over using the stated WTP, with the same data.

Keywords: Machine Learning, Willingness to Pay, BDM, Random Forest, Lasso, Prediction

JEL Classification: C81, C91, D12

Suggested Citation

Clithero, John A. and Lee, Jae Joon and Tasoff, Joshua, Supervised Machine Learning for Eliciting Individual Demand (February 1, 2021). Available at SSRN: https://ssrn.com/abstract=3380039 or http://dx.doi.org/10.2139/ssrn.3380039

John A. Clithero (Contact Author)

Lundquist College of Business, University of Oregon ( email )

Lundquist College of Business
1208 University of Oregon
Eugene, OR 97403
United States

Jae Joon Lee

Claremont Colleges - Claremont Graduate University ( email )

150 E. Tenth Street
Claremont, CA 91711
United States

Joshua Tasoff

Claremont Colleges - Claremont Graduate University ( email )

150 E. Tenth Street
Claremont, CA 91711
United States

HOME PAGE: http://sites.cgu.edu/tasoffj/

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