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Journal Article
Underemployment Following the Great Recession and the COVID-19 Recession
The underemployment rate, the percent of employed people who are working part-time but prefer to be working full-time, moves closely with the unemployment rate, rising during recessions and falling during expansions. Following the Great Recession, the underemployment rate had stayed persistently elevated when compared to the unemployment rate, that is, until the COVID-19 recession. Since then, it has been consistent with its pre-2008 levels. We find that changes in relative industry size account for essentially none of the underemployment rate increase after the Great Recession nor the ...
Journal Article
Residual Seasonality in Five Measures of PCE Inflation
I document residual seasonality in five measures of PCE inflation: headline, core, market-based core, median, and trimmed mean. While these measures are all computed from seasonally adjusted data, I show that each of these measures has had low average monthly inflation in November and December and high average monthly inflation in January from 1987 through the beginning of 2025. The difference in inflation rates from November and December to January is economically and statistically significant. This timing for residual seasonality often gives the impression that monthly inflation is low at ...
Working Paper
Understanding the Aspects of Federal Reserve Forward Guidance
This paper studies the effects of Federal Open Market Committee (FOMC) forward guidance language. I estimate two policy surprises at FOMC meetings: a change in the current federal funds rate and an orthogonal change in the expected path of the federal funds rate. From February 2000 to June 2003, the FOMC only gave forward guidance about risks to the economic outlook, and a surprise increase in the expected federal funds rate path had expansionary effects. This is consistent with models of central bank information effects, where a positive economic outlook causes private agents to revise up ...
Journal Article
The Discrepancy Between Expenditure- and Income-Side Estimates of US Output
The United States has two measures of economic output: gross domestic product (GDP) and gross domestic income (GDI). While these are conceptually equivalent, their initial estimates differ because these initial estimates are computed from different and incomplete data sources. I study the difference, or “statistical discrepancy,” between GDP and GDI in percent and document three features. First, its size does not materially shrink on average as more data become available. Second, the size of the initial discrepancy in absolute value does not predict the size of the discrepancy in absolute ...
Working Paper
An Empirical Evaluation of Some Long-Horizon Macroeconomic Forecasts
We use long-run annual cross-country data for 10 macroeconomic variables to evaluate the long-horizon forecast distributions of six forecasting models. The variables we use range from ones having little serial correlation to ones having persistence consistent with unit roots. Our forecasting models include simple time series models and frequency domain models developed in Müller and Watson (2016). For plausibly stationary variables, an AR(1) model and a frequency domain model that does not require the user to take a stand on the order of integration appear reasonably well calibrated for ...
Working Paper
Monetary Policy, Residential Investment, and Search Frictions: An Empirical and Theoretical Synthesis
Using a factor-augmented vector autoregression (FAVAR), this paper shows that residential investment contributes substantially to GDP following monetary policy shocks. Further, it shows that the number of new housing units built, not changes in the sizes of existing or new housing units, drives residential investment fluctuations. Motivated by these results, this paper develops a dynamic stochastic general equilibrium (DSGE) model where houses are built in discrete units and traded through searching and matching. The search frictions transmit shocks to housing construction, making them ...
Working Paper
The Effects of the Federal Reserve Chair’s Testimony on Interest Rates and Stock Prices
We study how congressional testimony about monetary policy by the Chair of the Board of Governors of the Federal Reserve System affects interest rates and stock prices. First, we study testimony associated with the Federal Reserve’s Monetary Policy Reports (MPRs) to Congress. Testimony for a particular MPR is usually given on two days, one day for each chamber of Congress. We separately study the first day and second day of MPR testimony. We also study testimonies not associated with MPRs but that are still related to monetary policy. We find that first-day MPR testimonies cause the largest ...
Journal Article
Can Yield Curve Inversions Be Predicted?
An inverted Treasury yield curve?a yield curve where short-term Treasury interest rates are higher than long-term Treasury interest rates?is a good predictor of recessions. Because of this, economists and policymakers often assess the risk of a yield curve inversion when the yield curve is flattening. I study the forecastability of yield curve inversions. Professional forecasters did not predict the beginning of the yield curve inversions prior to the 1990?1991, 2001, and 2008?2009 recessions. In all three cases, professional forecasters failed to predict the magnitude of the rise in ...
Working Paper
Proxy SVARs: Asymptotic Theory, Bootstrap Inference, and the Effects of Income Tax Changes in the United States
Proxy structural vector autoregressions (SVARs) identify structural shocks in vector autoregressions (VARs) with external proxy variables that are correlated with the structural shocks of interest but uncorrelated with other structural shocks. We provide asymptotic theory for proxy SVARs when the VAR innovations and proxy variables are jointly ?-mixing. We also prove the asymptotic validity of a residual-based moving block bootstrap (MBB) for inference on statistics that depend jointly on estimators for the VAR coefficients and for covariances of the VAR innovations and proxy variables. These ...
Working Paper
Random Walk Forecasts of Stationary Processes Have Low Bias
We study the use of a zero mean first difference model to forecast the level of a scalar time series that is stationary in levels. Let bias be the average value of a series of forecast errors. Then the bias of forecasts from a misspecified ARMA model for the first difference of the series will tend to be smaller in magnitude than the bias of forecasts from a correctly specified model for the level of the series. Formally, let P be the number of forecasts. Then the bias from the first difference model has expectation zero and a variance that is O(1/P-squared), while the variance of the bias ...