Similarly, in pricing TIPS, a trader with a nonconformist view faces costs in taking that view, so even if ultimately proven correct, the costs of establishing such a position may deter the nonconformist view’s from being reflected in market prices. Second, professional forecasters may be overly exposed to similar “world views,” sharing similar data, reports, and analyses. This may lead to an information aggregation bias of sorts, in which forecasters share the same information set, which is an aggregate of finer information, and which may result in the loss of some important information. The next charts describe the median four-quarter-ahead CPI forecast and the dispersion around that median for the Blue Chip survey and the U.S. Survey of Professional Forecasters. While there is significant overlap in the two sets of respondents, there is an important difference between the two surveys: respondents are anonymous in the U.S. Survey of Professional Forecasters, whereas they are identified by name in the Blue Chip survey. The asymmetric payoffs described earlier may therefore have more of an impact in the Blue Chip survey than in the U.S. Survey of Professional Forecasters, leading to less dispersion in the former than in the latter. Chart 9 shows that the median forecast is substantially the same across the two surveys. However, as seen in Chart 10, there is some evidence of lower heterogeneity among forecasters in the Blue Chip survey compared with the Survey of Professional Forecasters, especially in recent periods, which, in retrospect, were periods of high fundamental uncertainty in the economy.
We also report home price change expectations and price change expectations for various commodities. In our latest survey in May 2014, these expectations remained stable for the most part. Interestingly, medical care price change expectations have been gradually declining since December 2013, dropping from around 11 percent to 9.5 percent. The expected cost of a college education has also been dropping since the start of 2014. These results are shown in Charts 2 and 3. For the labor market, we report the median expected earnings growth over the next twelve months. This figure has been stable at around 2 percent over the sample period, with a small increase to 2.4 percent over the winter that has since been reversed, as seen in Chart 4. We also track workers’ perceived chances of losing their current job, of leaving their current job voluntarily, and of finding another job in three months should they lose their current one. Quits, layoffs, and the job-finding rate are important flow measures, and workers’ expectations about these events enable us to gauge households’ perceptions of future labor market conditions. As I will mention later, these expectations seem to be meaningfully related to job search behavior and other economic decisions by households.