These include sticky information models, in which new information is slow to diffuse through the population (Mankiw and Reis, 2002), perhaps because agents only probabilistically pay attention to experts or to news (Carroll, 2003). They also include noisy information models, in which agents form expectations based on noisy private signals (Woodford, 2001). Other explanations are based on the use of some form of adaptive learning (Evans and Honkapohja, 2001), switching between different prediction rules (Branch, 2004); or learning from lifetime inflation experiences (Malmendier and Nagel, 2013; Madeira and Zafar, 2012). In our information-based experiment that I discussed earlier, we found that cross-sectional disagreement (variance) in expectations falls after our information treatments, which is consistent with a sticky-information model and points to the importance of private information and information constraints. We also found evidence of gender differences in updating behavior, which in turn may reflect differences in gathering and evaluating new information. Numeracy, financial literacy, and education also appear to play a role in explaining dispersion across respondents, as seen in Chart 8. In our research, we have found extreme inflation expectations, especially high values, to be associated with lower financial literacy and numeracy skills, and with being relatively under-informed about past inflation or inflationrelated facts. Finally, there exists suggestive evidence of respondents forecasting under asymmetric loss, with respondents appearing to be averse to under-estimating inflation.
Having a panel reduces the variability induced by changes in composition month to month and increases the precision of any measured changes in expectations. Before we implemented the survey, our proposal was reviewed and approved by the Bank’s senior management. Next, we issued a request for proposals and received three bids from independent survey organizations to field our survey design. In the end, we chose to work with the Demand Institute, a partnership of the Conference Board and Nielsen. The resulting Survey of Consumer Expectations is a nationally representative monthly internet-based survey. Its rotating panel consists of about 1,200 household heads. We find that the internet approach allows us a great deal of flexibility to ask new questions, and it BIS central bankers’ speeches  1  makes it considerably easier to pose probabilistic questions and to run experiments. It is also – and this is an important consideration – the most cost-effective mode of collection; at the same time, there is also some evidence of higher response accuracy to personally sensitive questions. Our sample is based on the Conference Board’s Consumer Confidence Survey sample, which is drawn from U.S. postal addresses. Respondents are compensated with a payment of $ per survey, and surveys vary in length from fifteen to thirty minutes. Our firsttime response rate is about 60 percent, and we find that respondents have somewhat greater-than-average education and income. The average response rate among repeat respondents is more than 80 percent.