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Working Paper
The FOMC versus the Staff: Do Policymakers Add Value in Their Tales?
Using close to 40 years of textual data from FOMC transcripts and the Federal Reserve staff's Greenbook/Tealbook, we extend Romer and Romer (2008) to test if the FOMC adds information relative to its staff forecasts not via its own quantitative forecasts but via its words. We use methods from natural language processing to extract from both types of document text-based forecasts that capture attentiveness to and sentiment about the macroeconomy. We test whether these text-based forecasts provide value-added in explaining the distribution of outcomes for GDP growth, the unemployment rate, and ...
Working Paper
Heterogeneity in Household Inflation Expectations: Policy Implications
We empirically characterize the heterogeneity in the conditional distribution of household inflation expectations across demographic groups using the Survey of Consumer Expectations and investigate how monetary policy shocks affect the conditional distribution. We find that across all demographic groups, the peak of the group-specific distribution of household inflation expectations aligns closely with the Federal Reserve’s 2 percent target. However, we also find substantial heterogeneity both within and across groups, primarily on the right end of the distribution. Nevertheless, we show ...
Report
Nonlinear Binscatter Methods
Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily construct flexible yet interpretable visualization methods, but they can also be used to estimate treatment effects, assess uncertainty, and test substantive domain-specific hypotheses. This paper introduces novel binscatter methods based on nonlinear, possibly nonsmooth M-estimation methods, covering generalized linear, robust, and quantile ...