These patterns are robust to other approaches of measuring belief wedges, such as replacing the statistical forecast with forecasts from the Survey of Professional Forecasters or replacing the household forecasts with those from the Federal Reserve Bank of New York Survey of Consumer Expectations. Third, the wedges tend to be higher during periods of lower GDP growth. Second, these wedges are positively and significantly correlated.
First, households forecast higher unemployment and higher inflation on average, relative to the statistical forecast, with mean belief wedges of 0.58 percent and 1.25 percent, respectively, over the sample period. Again, based on evidence from the Bank of England survey, we interpret positive values in Figure 1 as indicators of pessimism and negative values in Figure 1 as indicators of optimism. We plot the resulting belief wedges in Figure 1 for both inflation and unemployment. To derive belief wedges, we compare these household forecasts to a statistical forecast from a vector autoregression (VAR) for the first quarter of 1982 through the fourth quarter of 2015. We obtain data on households' expectations from the Michigan survey, which interviews households about their views on current and future economic conditions. In addition, a fear of higher future costs reduces incentives for firms to lower prices despite lower demand from households. Pessimism affects the macroeconomy through households reducing current demand and firms posting fewer job vacancies. In particular, fluctuations in pessimism account for a large fraction of the variation in unemployment. The model reveals that pessimism has important effects on the aggregate economy. Furthermore, increases in pessimism lead to larger upward biases for both unemployment and inflation and are accompanied by an economic contraction. This explains the average upward biases in household forecasts of unemployment and inflation. Although our theory allows for optimism, we find that household survey data are consistent with pessimism on average. This time-varying pessimism and optimism provides a parsimonious way to match all our documented empirical facts.
In contrast to the rational-expectations framework, in which the expectations of economic agents equal the model-implied forecasts, pessimistic households in our model overestimate (and optimistic households underestimate) the probability of adverse future outcomes relative to the model-implied forecast. We develop a quantitative model of time-varying pessimism and optimism that is consistent with these facts.
In line with evidence from the Bank of England/Kantar Inflation Attitudes Survey linking higher inflation to lower expectations of economic conditions, we interpret the forecasts of higher unemployment and inflation as pessimism. We refer to this difference between the household and statistical (or rational) forecasts as a "belief wedge." Furthermore, in the cross section, households that expect higher inflation relative to the population also tend to expect higher unemployment. 1 Using the University of Michigan Surveys of Consumers (Michigan survey), we show that household forecasts for unemployment and inflation are biased upward on average relative to a statistical forecast and that both biases increase significantly during recessions. In a recent working paper, we document systematic biases in household forecasts for unemployment and inflation in both time-series and cross-sectional data. Survey data allow us to measure how the expectations of different economic agents fluctuate over time, providing evidence to test theories of expectation formation and allowing us to quantify their effects. These individual decisions can lead to aggregate fluctuations in output, employment and prices. For instance, a more pessimistic outlook can lead households to save more and firms to hire less.
INFLATION ARE REASONS OPTIMISM. DRIVERS
Expectations about the future are important drivers of the economy.
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