Foundations and Trends® in Econometrics > Vol 10 > Issue 1-2

Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis

Moshe Ben-Akiva, MIT, USA, mba@mit.edu Daniel McFadden, University of California, Berkeley and USC, USA, mcfadden@econ.berkeley.edu Kenneth Train, University of California, Berkeley, USA, Kenneth.Train@nera.com
 
Suggested Citation
Moshe Ben-Akiva, Daniel McFadden and Kenneth Train (2019), "Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis", Foundations and TrendsĀ® in Econometrics: Vol. 10: No. 1-2, pp 1-144. http://dx.doi.org/10.1561/0800000036

Published: 28 Jan 2019
© 2019 Moshe Ben-Akiva, Daniel McFadden and Kenneth Train
 
Subjects
Duration models,  Conjoint Analysis,  Discrete choice models
 
Keywords
B23C25C35C53C83D12
Econometric methodschoice-based conjoint analysis (CBC)stated preference elicitationdiscrete choice methods
 

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In this article:
Preface
1. Some History of Stated Preference Elicitation
2. Choice-Based Conjoint (CBC) Analysis
3. Choice Behavior
4. Choice Model Estimation and Forecasting with CBC Data
5. Maximum Simulated Likelihood (MSL) Analysis of CBC Data
6. Hierarchical Bayes Estimation
7. An Empirical CBC Study Using MSL and HB Methods
8. An Application with Inter and Intra-consumer Heterogeneity
9. Policy Analysis
10. Conclusions
Appendix
Acknowledgements
References

Abstract

Stated preference elicitation methods collect data on consumers by "just asking" about tastes, perceptions, valuations, attitudes, motivations, life satisfactions, and/or intended choices. Choice-Based Conjoint (CBC) analysis asks subjects to make choices from hypothetical menus in experiments that are designed to mimic market experiences. Stated preference methods are controversial in economics, particularly for valuation of non-market goods, but CBC analysis is accepted and used widely in marketing and policy analysis. The promise of stated preference experiments is that they can provide deeper and broader data on the structure of consumer preferences than is obtainable from revealed market observations, with experimental control of the choice environment that circumvents the feedback found in real market equilibria. The risk is that they give pictures of consumers that do not predict real market behavior. It is important for both economists and non-economists to learn about the performance of stated preference elicitations and the conditions under which they can contribute to understanding consumer behavior and forecasting market demand. This monograph re-examines the discrete choice methods and stated preference elicitation procedures that are commonly used in CBC, and provides a guide to techniques for CBC data collection, model specification, estimation, and policy analysis. The aim is to clarify the domain of applicability and delineate the circumstances under which stated preference elicitations can provide reliable information on preferences.

DOI:10.1561/0800000036
ISBN: 978-1-68083-526-7
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Table of contents:
Preface
1. Some History of Stated Preference Elicitation
2. Choice-Based Conjoint (CBC) Analysis
3. Choice Behavior
4. Choice Model Estimation and Forecasting with CBC Data
5. Maximum Simulated Likelihood (MSL) Analysis of CBC Data
6. Hierarchical Bayes Estimation
7. An Empirical CBC Study Using MSL and HB Methods
8. An Application with Inter and Intra-consumer Heterogeneity
9. Policy Analysis
10. Conclusions
Appendix
Acknowledgements
References

Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis

Foundations of Stated Preferences Elicitation provides the reader with stated preference data collection methods, discrete choice models, and statistical analysis tools that can be used to forecast demand and assess welfare impacts for new or modified products or services in real markets, and summarize the conditions under which the reliability of these methods has been demonstrated or can be tested. One focus is the collection of preference and related data from consumer responses in hypothetical choice experiments, particularly conjoint analysis methods that have proven useful in market research. Another is the economic theory and statistical analysis of choice behavior, revealed or stated, and an economic framework for forecasting market demand and measuring consumer welfare. The treatment is informed by and benefits from experiments on perceptions and decision-making behavior in cognitive science and behavioral economics, and includes methods that can accommodate features of consumer choice that impact forecast reliability such as anchoring, adaptation to the status quo, and sensitivity to context. However, the authors' emphasis is on forecasting tools developed from traditional economic consumer theory and does not touch on the implications of behavioral consumer theory for demand forecasting.

 
ECO-036