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Drawing from recent developments in social cognition, cognitive psychology, and behavioral decision theory, we analyzed when and how the act of measuring beliefs, attitudes, intentions, and behaviors affects observed correlations among them. Belief, attitude, or intention can be created by measurement if the measured constructs do not already exist in long-term memory. The responses thus created can have directive effects on answers to other questions that follow in the survey. But even when counterparts to the beliefs, attitudes, and intentions measured already exist in memory, the structure of the survey researcher's questionnaire can affect observed correlations among them. The respondent may use retrieved answers to earlier survey questions as inputs to response generation to later questions. We present a simple theory predicting that an earlier response will be used as a basis for another, subsequent response if the former is accessible and if it is perceived to be more diagnostic than other accessible inputs. We outline the factors that determine both the perceived diagnosticity of a potential input, the likelihood that it will be retrieved, and the likelihood that some alternative (and potentially more diagnostic) inputs will be retrieved.

Policy makers have embraced financial education as a necessary antidote to the increasing complexity of consumers' financial decisions over the last generation. We conduct a meta-analysis of the relationship of financial literacy and of financial education to financial behaviors in 168 papers covering 201 prior studies. We find that interventions to improve financial literacy explain only 0.1% of the variance in financial behaviors studied, with weaker effects in low-income samples. Like other education, financial education decays over time; even large interventions with many hours of instruction have negligible effects on behavior 20 months or more from the time of intervention. Correlational studies that measure financial literacy find stronger associations with financial behaviors. We conduct three empirical studies, and we find that the partial effects of financial literacy diminish dramatically when one controls for psychological traits that have been omitted in prior research or when one uses an instrument for financial literacy to control for omitted variables. Financial education as studied to date has serious limitations that have been masked by the apparently larger effects in correlational studies. We envisage a reduced role for financial education that is not elaborated or acted upon soon afterward. We suggest a real but narrower role for “just-in-time” financial education tied to specific behaviors it intends to help. We conclude with a discussion of the characteristics of behaviors that might affect the policy maker's mix of financial education, choice architecture, and regulation as tools to help consumer financial behavior. This paper was accepted by Uri Gneezy, behavioral economics.

The authors examine the implications of electronic shopping for consumers, retailers, and manufacturers. They assume that near-term technological developments will offer consumers unparalleled opportunities to locate and compare product offerings. They examine these advantages as a function of typical consumer goals and the types of products and services being sought and offer conclusions regarding consumer incentives and disincentives to purchase through interactive home shopping vis-à-vis traditional retail formats. The authors discuss implications for industry structure as they pertain to competition among retailers, competition among manufacturers, and retailer-manufacturer relationships.

It is common for researchers discovering a significant interaction of a measured variable X with a manipulated variable Z to examine simple effects of Z at different levels of X. These “spotlight” tests are often misunderstood even in the simplest cases, and it appears that consumer researchers are unsure how to extend them to more complex designs. The authors explain the general principles of spotlight tests, show that they rely on familiar regression techniques, and provide a tutorial demonstrating how to apply these tests across an array of experimental designs. Rather than following the common practice of reporting spotlight tests at one standard deviation above and below the mean of X, it is recommended that when X has focal values, researchers should report spotlight tests at those focal values. When X does not have focal values, it is recommended that researchers report ranges of significance using a version of Johnson and Neyman's test the authors term a “floodlight.”