We examine the evolution of consumers’ expectations for their post-crisis spending on services that have been dramatically curtailed by the pandemic: visiting restaurants, bars, and hotels, using public transportation, and attending crowded events. While most groups now plan to return to their previous spending on these services, higher-income individuals expect to sharply increase their use of these services, but older Americans expect to lower theirs.  Read More

This Commentary examines the response of longer-run inflation expectations to the FOMC’s August 2020 announced switch to a flexible average inflation-targeting (FAIT) regime.   Read More

To provide insights into the processes that drive inflationary dynamics, the Federal Reserve Bank of Cleveland holds an annual conference on the topic of inflation: the Inflation: Drivers and Dynamics series. The 2020 installment of the conference was held on May 21-22, 2020. This Commentary summarizes the papers at the conference, which broadly fell into four categories: (1) empirical Phillips curves, (2) networks and Phillips curves, (3) expectations formation, and (4) price-setting behavior and inflation.  Read More

Statistical agencies track rental expenditures for use in the national accounts and in consumer price indexes (CPIs). As such, statistical agencies should include late payment fees and nonpayment in rent. In the US context, late payment fees are excluded from the CPI. Ostensibly, nonpayment of rent is included in the US CPI; but its treatment is deficient, and we demonstrate that small variations in nonpayment could lead to large swings in shelter inflation, and might have played a role in the 2009 measured shelter inflation collapse. They didn’t: while the national nonpayment incidence is 2-3 percent, in the 1 million plus rent observations in BLS rent microdata from 2000-2016, no nonpayment is recorded. A back-of-the-envelope calculation suggests that, assuming nonpayment undermeasurement continued after 2016, CPI shelter inflation may have been overestimated by about 1 percentage point per month (annualized) in 2020. Late fees and nonpayment are difficult to measure in real time. We offer implementation suggestions that are consistent with CPI procedures.  Read More

This paper examines data from the European Central Bank’s Survey of Professional Forecasters to investigate whether participants display equal predictive performance. We use panel data models to evaluate point- and density-based forecasts of real GDP growth, inflation, and unemployment. The results document systematic differences in participants’ forecast accuracy that are not time invariant, but instead vary with the difficulty of the forecasting environment. Specifically, we find that some participants display higher relative accuracy in tranquil environments, while others display higher relative accuracy in volatile environments. We also find that predictive performance is positively correlated across target variables and horizons, with density forecasts generating stronger correlation patterns. Taken together, the results support the development of expectations models featuring persistent heterogeneity.  Read More

Housing rents are a large share of household budgets and make a large contribution to overall inflation. Rent inflation rates for different types of housing units sometimes diverge, even in the same neighborhoods. We estimate during 2013 to 2016 apartment rents outpaced rents for detached housing in the United States by 0.76 percentage points annually after controlling for location effects. These rent dynamics imply a segmented housing market. They also suggest rent indexes need to be based on data structurally representative of their measurement objective. In particular, indexes based on professionally managed apartment complexes mismeasure the rents for housing generally. Even indexes based on careful geographical sampling, such as the Consumer Price Index’s Owners’ Equivalent Rent component, may be biased by using an unrepresentative mix of apartments and houses.  Read More