Not Available for Download

Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments

Political Analysis (Winter 2014) 22 (1): 1-30

Posted: 11 Mar 2013 Last revised: 29 Jan 2014

Jens Hainmueller

Stanford University - Department of Political Science; Stanford Graduate School of Business; Stanford Immigration Policy Lab

Daniel J. Hopkins

University of Pennsylvania

Teppei Yamamoto

Massachusetts Institute of Technology (MIT) - Department of Political Science

Date Written: November 5, 2013

Abstract

Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and assess several causal hypotheses simultaneously. In conjoint analysis, respondents score a set of alternatives, where each has randomly varied attributes. Here, we undertake a formal identification analysis to integrate conjoint analysis with the potential outcomes framework for causal inference. We propose a new causal estimand and show that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design. We then demonstrate the value of these techniques through empirical applications to voter decision-making and attitudes toward immigrants.

Keywords: potential outcomes, average marginal component effects, conjoint analysis, survey experiments, public opinion, vote choice, immigration

JEL Classification: C35, C42, M3, C8, C9

Suggested Citation

Hainmueller, Jens and Hopkins, Daniel J. and Yamamoto, Teppei, Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments (November 5, 2013). Political Analysis (Winter 2014) 22 (1): 1-30. Available at SSRN: https://ssrn.com/abstract=2231687 or http://dx.doi.org/10.2139/ssrn.2231687

Jens Hainmueller (Contact Author)

Stanford University - Department of Political Science ( email )

Stanford, CA 94305
United States

HOME PAGE: http://www.stanford.edu/~jhain/

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

Stanford Immigration Policy Lab

30 Alta Road
Stanford, CA 94305
United States

Daniel J. Hopkins

University of Pennsylvania ( email )

Stiteler Hall
Philadelphia, PA 19104
United States

HOME PAGE: http://www.danhopkins.org

Teppei Yamamoto

Massachusetts Institute of Technology (MIT) - Department of Political Science ( email )

77 Massachusetts Avenue
Cambridge, MA 02139
United States

Paper statistics

Abstract Views
2,205