This paper focuses on the implications of alternative methods of aggregating individual wage data for the behavior of economy-wide wage growth. The analysis is motivated by evidence of significant heterogeneity in individual wage growth and its cyclicality. Because of this heterogeneity, the choice of aggregation will affect the properties of economy-wide wage growth measures. To assess the importance of this consideration, we provide a decomposition of wage growth into aggregation effects and composition effects and use the decomposition to compare growth in an average wage—specifically average hourly earnings—to a measure of average wage growth from the Survey of Income and Program Participation. We find that aggregation effects largely account for average hourly earnings growth being persistently lower and less cyclical than average wage growth over the period 1990-2015, with these effects reflecting a disproportionate weighting of high-earning workers. The analysis also indicates that composition effects now play a more limited role in the cyclicality of wage growth compared to results reported in previous studies for earlier time periods.
This chapter provides an overview of surveys of professional forecasters, with a focus on the U.S. Survey of Professional Forecasters and the European Central Bank Survey of Professional Forecasters. A distinguishing feature of these surveys is that they collect point and density forecasts and make the data publicly available. We discuss their structure, issues involved in using the data, and the construction of measures such as disagreement and uncertainty at the aggregate and individual levels. Our review also summarizes the findings of studies exploring issues such as the alignment of point forecasts with measures of central tendency from associated density forecasts, the coverage of density forecasts, the rounding of point and density forecasts, comparisons of forecast accuracy across respondents, and heterogeneity in forecast behavior and the persistence of these differential features. We conclude with some observations for future work.
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.
This paper examines point and density forecasts of real GDP growth, inflation and unemployment from the European Central Bank’s Survey of Professional Forecasters. We present individual uncertainty measures and introduce individual point- and density-based measures of disagreement. The data indicate substantial heterogeneity and persistence in respondents’ uncertainty and disagreement, with uncertainty associated with prominent respondent effects and disagreement associated with prominent time effects. We also examine the co-movement between uncertainty and disagreement and find an economically insignificant relationship that is robust to changes in the volatility of the forecasting environment. This provides further evidence that disagreement is not a reliable proxy for uncertainty.
A new measure of inflation expectations’ anchoring finds that medium-run expectations weakened notably during the pandemic before strengthening again recently.
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.
Wage growth is often measured by the change in average hourly earnings (AHE), a gauge of overall wages that aggregates information on earnings and hours worked across individuals. A close look at this aggregation method demonstrates that AHE growth reflects disproportionately the profile of high-earning workers who typically display lower and less cyclically sensitive wage growth. Using data from the Current Population Survey (CPS), we adopt a different aggregation method and compute wage growth as the average of individuals’ wage growth. The analysis indicates that the CPS measure of average wage growth is significantly higher than AHE growth and that it displays a more meaningful nonlinear relationship with the Congressional Budget Office’s unemployment gap. Last, our findings do not support the claim that there was hidden slack in the labor market during the recent expansion that was restraining wage growth.
