The Use of Intentions Data to Predict Behavior: A Best-Case Analysis

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Abstract
In surveys individuals are routinely asked to predict their future behavior, that is, to state their intentions. This article studies the relationship between stated intentions and subsequent behavior under the “best-case” hypothesis that individuals have rational expectations and that their responses to intentions questions are best predictions of their future behavior. The objective is to place an upper bound on the behavioral information contained in intentions data and to determine whether prevailing approaches to the analysis of intentions data respect the bound. The analysis focuses on the simplest form of intentions questions, those that call for yes/no predictions of binary outcomes. The article also discusses “forced-choice” questions, which are distinct from, but are sometimes confused with, intentions questions. A primary lesson is that not too much should be expected of intentions data. It is shown that intentions data bound but do not identify the probability that a person will behave in a given way. The derived bounds are nonparametrically estimable and may be used to test the best-case hypothesis. Contrary to assertions in the literature, there is no reason to think that individual-level differences between intentions and behavior should “average out” in the aggregate.

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