Brent Meyer

Trimmed-Mean Inflation Statistics: Just Hit the One in the Middle

This paper reinvestigates the performance of trimmed-mean inflation measures some 20 years since their inception, asking whether there is a particular trimmed-mean measure that dominates the median consumer price index (CPI). Unlike previous research, we evaluate the performance of symmetric and asymmetric trimmed means using a well known equality of prediction test. We find that there is a large swath of trimmed means that have statistically indistinguishable performance. Also, although the swath of statistically similar trims changes slightly over different sample periods, it always includes the median CPI - an extreme trim that holds conceptual and computational advantages. We conclude with a simple forecasting exercise that highlights the advantage of the median CPI (and trimmed-mean estimators in general) relative to other standard measures in forecasting headline inflation.

The Inflation Expectations of Firms: What Do They Look Like, are They Accurate, and Do They Matter?

The purpose of this paper is to answer the three questions in the title. Using a large monthly survey of businesses, we investigate the inflation expectations and uncertainties of firms. We document that, in the aggregate, firm inflation expectations are very similar to the predictions of professional forecasters for national inflation statistics, despite a somewhat greater heterogeneity of expectations that we attribute to the idiosyncratic cost structure firms face. We also show that firm inflation expectations bear little in common with the “prices in general” expectations reported by households. Next we show that, during our three-year sample, firm inflation expectations appear to be unbiased predictors of their year-ahead observed (perceived) inflation. We also show that firms know what they don’t know—that the accuracy of firm inflation expectations is significantly and negatively related to their uncertainty about future inflation. And lastly, we demonstrate, by way of a cross-sectional Phillips curve, that firm inflation expectations are a useful addition to a policymaker’s information set. We show that firms’ inflation perceptions depend (importantly) on their expectations for inflation and their perception of firm-level slack.

Lessons for Forecasting Unemployment in the U.S.: Use Flow Rates, Mind the Trend

This paper evaluates the ability of autoregressive models, professional forecasters, and models that leverage unemployment flows to forecast the unemployment rate. We pay particular attention to flows-based approaches—the more reduced form approach of Barnichon and Nekarda (2012) and the more structural method in Tasci (2012)—to generalize whether data on unemployment flows is useful in forecasting the unemployment rate. We find that any approach that leverages unemployment inflow and outflow rates performs well in the near term. Over longer forecast horizons, Tasci (2012) appears to be a useful framework, even though it was designed to be mainly a tool to uncover long-run labor market dynamics such as the “natural” rate. Its usefulness is amplified at specific points in the business cycle when unemployment rate is away from the longer-run natural rate. Judgmental forecasts from professional economists tend to be the single best predictor of future unemployment rates. However, combining those guesses with flows based approaches yields significant gains in forecasting accuracy.