Behavioral Biases in Household Fiancial Decision-Making
We can summarize the fundamental findings of modern behavioral economics as a small set of what have come to be called “behavioral biases.” These biases are systematic departures from rational norms that many people exhibit in the face of economic decisions. For example, “present bias” refers to one’s difficulty in postponing immediate returns. A person who would happily choose to wait longer when faced with a choice between $100 in 52 weeks and $125 in 54 weeks might nevertheless find it difficult to wait when the choice is between $100 immediately and $125 two weeks from now. The demonstration and analysis of behavioral biases such as these is a significant advance over earlier behavioral critiques of standard economic theory, which pointed out that fully rational decision-making is “bounded” by limited cognitive capacity, but failed to develop a rich account of the systematic ways in which people depart from rationality.
Behavioral biases have typically been studied one by one—by carefully constructing artificial choice problems that reveal their effects. Now that behavioral economics is beginning to apply itself to the practical problems of helping people to overcome their behavioral biases in the face of real economic decisions, behavioral biases can no longer be effectively studied in isolation. As Jonathan Zinman points out, we need to understand more about how biases correlate with each other in the population at large and how they interact in everyday decision-making. A mortgage, for example, is a complex financial contract; the decision about which kind of mortgage to enter into may well be subject to several different biases simultaneously. So, people suffering from present bias might be especially vulnerable to balloon mortgages that start with a low teaser rate. This vulnerability might be amplified if these people also suffer from overconfidence—a common bias that could lead people to believe that they can refinance before a higher rate sets in. On the other hand, if these people are more likely to suffer from loss aversion than overconfidence, balloon mortgages might seem too risky despite the attractive initial rate.
With support from the Russell Sage Foundation, Jonathan Zinman (Dartmouth College), Victor Stango (University of California, Davis), and Joanne Su-Yin Yoong (RAND Corporation) will conduct a study that measures correlations like these by embedding diagnostic tests for approximately fifteen prominent behavioral biases in two nationally representative, web-based consumer survey panels: the RAND Corporation’s American Life Panel, and the Ultimate Consumer Panel maintained by Lightspeed Research. These panels contain rich data on respondents’ financial behavior and financial condition, in addition to standard demographics. Because the RAND panel is nationally representative, it will allow the principal investigators to estimate the prevalence of each bias in the population at large and analyze the correlations between biases, taking into account a standard set of demographic controls. Since both of these consumer panels contain a wealth of survey and administrative information about the financial lives of the respondents, the researchers will be able to assess the strength of the relationships between each of the biases and a rich battery of measures of financial behavior and financial well-being. If found, such correlations could help guide the design of interventions to help people make better decisions. Such correlations could also be useful for building and testing behavioral models. If there is one bias with particularly strong correlations with other biases and with behavior, then it could serve as a summary statistic to index individual differences in general financial acuity or vulnerability.
The investigators also propose to use the consumer panels to try to develop an overall measure of financial well-being. By developing survey questions on self-reported financial condition and correlating these self-reports with rich administrative data on financial behavior and outcomes available in the Lightspeed panel, the group believes that they may be able to produce a single, reliable measure of an individual’s financial condition.