Market rates and probability forecasts It is well understood in theory why the market-implied path of the policy rate usually differs from survey measures of policy expectations.50 Even if the marginal investor’s probability distribution for future outcomes coincided with that of the average survey respondent, she would want additional compensation for bearing risk in states of the world that are unfavorable to her. It is conceivable in the current environment that outcomes in which the federal funds rate would return to the zero lower bound, or more generally remain low, are not good news for the overall portfolio of the marginal investor. Thus, in assessing the price at which she would be willing to trade interest rate derivatives like federal funds futures, she would weight those “negative” states of the world, such as states involving a return to the zero lower bound, more than her subjective probability distribution would imply – and the opposite would hold true for “positive” states of the world. In other words, in this environment the risk premium compensation she requires would pull the market-implied path downward, away from survey expectations. While risk premia, especially at this juncture, are likely very important, looking only at pointforecasts may overemphasize their role when these point forecasts coincide with modal forecasts. In particular, when the implied policy rate from federal funds or Eurodollar futures changes, while the point forecasts from surveys do not, it is customary to attribute all the change in the market rates to risk premia.

To our knowledge, these results provide the first direct evidence regarding a meaningful link between survey-based inflation expectations and actual behavior.32 In the second experiment, we studied the formation process of inflation expectations by looking at whether and how survey respondents updated their inflation expectations when they received relevant new information.33 Specifically, we first elicited inflation expectations. We then randomly provided information to a subset of respondents on either past food price inflation, or professional economists’ forecasts of future inflation from the SPF. Finally, we reelicited respondents’ inflation expectations, and studied whether they were correlated with the information content of the signal they received.34 We found that respondents, on average, updated their inflation expectations in response to the information provided, and they did so sensibly and in a direction consistent with Bayesian updating – with larger revisions for less informed respondents and for those with greater baseline uncertainty. Further, there was significant heterogeneity both in how fully informed respondents were about objective inflation measures and in their updating behavior. This finding points to the potential importance of allowing for heterogeneous informationprocessing rules in our economic models. These findings are also consistent with existing sticky-information models of expectations formation, since cross-sectional disagreement falls after the provision of information.35 Results from the experiment also indicate that expectations about changes in the “prices you pay,” like the similar Michigan survey question about “prices in general,” are more responsive to information about food prices than expectations about the rate of inflation.