rather than disturb your lunch, we can instead consider using the wisdom of the market. given my role in the markets group at the new york fed, i'd like to focus on what financial market participants'beliefs and market prices can tell us about this question and what we should do with the answers from them. 8 let's first consider asking market participants directly and then use observed asset prices to answer the question. prior to the january 2019 fomc meeting, as part of its routine policy expectations survey, the new york fed asked market participants to report what percent chance they attach to the u. s. economy currently being in an nber recession, and what percent chance they attach to the u. s. economy being in an nber recession in six months. 9 we have been asking survey recipients 2 / 6 bis central bankers'speeches these questions for over 10 years. as shown in figure 1, the median respondent assigned a 2 percent probability to the u. s. currently being in a recession and a 12 percent probability to the u. s. being in a recession in six months, with a fairly small degree of dispersion around these predictions. separately, we posed a newer and more complicated question, asking respondents to provide a probability distribution of the timing at which they believe the u. s. economy will first enter a recession. the bubble chart shown in figure 2 illustrates the range of results, with the relative size of each bubble indicating the relative number of responses for each probability. perhaps not surprisingly, responses were much more dispersed. respondents placed the highest probability on a u. s. recession first occurring in 2020 or 2021, assigning a roughly 25 percent probability to each, on average. at about 17 percent, the distribution's average probability of a recession starting in 2019 or earlier suggests a good match with the shorter - horizon question. interestingly, our respondents demonstrated an ability to calibrate their probability assessments over a longer horizon, something some of tetlock's superforecasters struggled with. however, historical perspective may offer a cautionary tale. figure 3 shows the evolution of results from our survey's recurring questions on the probability that the u. s. economy is currently in an nber recession and that it will be in an nber recession in six months, taken over the mid2007 to late - 2008 time period. this period, of course, encompasses the start of the great recession, which the nber dated as beginning in

reason to extremize the results is that the prediction object is a recession in one particular month, rather than the probability of a recession over a period of time. marcelle chauvet and i analyzed this more general problem. 12 our goal was to avoid the problem with the probit model that a constant forecast of, for example, a 25 percent probability that the economy will be in 3 / 6 bis central bankers'speeches recession in 12 months'time implying after one year of such monthly predictions a 97 percent probability the economy would be in a recession in at least one month of the 12. this is similar to the issue i mentioned earlier, where some of the superforecasters appear to have had difficulty calibrating their probability assessments over varying time horizons. such a poor calibration would run afoul of the brier - based scoring system used in the iarpa tournament. 13 it is clear that extremizing the results lessens the impact of the poor calibration on the scoring system, but it leaves open the question of whether a better calibration is possible. another financial market indicator we could look at is the stock market. as paul samuelson famously stated, the stock market has predicted nine of the last five recessions. an alternative statement — and this is also true of yield curve inversions — is that no u. s. recession has occurred since the second world war without a yield curve inversion or stock market correction ( or worse ) proceeding it. as a recent san francisco fed economic letter carefully illustrated, yield curve inversions have the additional record of indicating only one false positive in the u. s., during the mid - 1960s. 14 if we cared equally about forecasting recessions and expansions, these properties would be well - reflected in the brier score ; however, if we view recessions — or more accurately, elevated probabilities of a recession — as more concerning than elevated probabilities of an expansion, then brier scoring is not sufficient. as tetlock writes, " one problem is that brier scores treat false alarms the same as misses. " the issue of asymmetric loss functions over outcomes is well understood by economists, and more recent research around robustness to ambiguity in probability assessments provides more formal methods of " extremizing " probabilities based on loss functions and the level of ambiguity. 15 another issue tetlock raises is that prediction of binary outcomes of clearly stated problems