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Working Paper
Inflation and Real Activity over the Business Cycle
We study the relation between inflation and real activity over the business cycle. We employ a Trend-Cycle VAR model to control for low-frequency movements in inflation, unemployment, and growth that are pervasive in the post-WWII period. We show that cyclical fluctuations of inflation are related to cyclical movements in real activity and unemployment, in line with what is implied by the New Keynesian framework. We then discuss the reasons for which our results relying on a Trend-Cycle VAR differ from the findings of previous studies based on VAR analysis. We explain empirically and ...
Working Paper
Deciphering Federal Reserve Communication via Text Analysis of Alternative FOMC Statements
We apply a natural language processing algorithm to FOMC statements to construct a new measure of monetary policy stance, including the tone and novelty of a policy statement. We exploit cross-sectional variations across alternative FOMC statements to identify the tone (for example, dovish or hawkish), and contrast the current and previous FOMC statements released after Committee meetings to identify the novelty of the announcement. We then use high-frequency bond prices to compute the surprise component of the monetary policy stance. Our text-based estimates of monetary policy surprises are ...
Working Paper
Improving GDP measurement: a measurement-error perspective
We provide a new and superior measure of U.S. GDP, obtained by applying optimal signal-extraction techniques to the (noisy) expenditure-side and income-side estimates. Its properties -- particularly as regards serial correlation -- differ markedly from those of the standard expenditure-side measure and lead to substantially-revised views regarding the properties of GDP.
Working Paper
Leaning Against the Data: Policymaker Communications under State-Based Forward Guidance
A purported benefit of state-based forward guidance is that the private sector adjusts the expected stance of policy without further policymaker communications. This assumes a shared understanding of how policymakers are interpreting the data and that policymakers are consistent in their assessment of the data. Using textanalysis, we test whether the FOMC’s introduction of state-based forward guidance in December 2012 changed the tone of policymaker communications. We find that policymakers tended to downplay positive data following the introduction of the guidance, in effect leaning ...
Working Paper
Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic
In this paper we resuscitate the mixed-frequency vector autoregression (MF-VAR) developed in Schorfheide and Song (2015) to generate real-time macroeconomic forecasts for the U.S. during the COVID-19 pandemic. The model combines eleven time series observed at two frequencies: quarterly and monthly. We deliberately do not modify the model specification in view of the recession induced by the COVID-19 outbreak. We find that forecasts based on a pre-crisis estimate of the VAR using data up until the end of 2019 appear to be more stable and reasonable than forecasts based on a sequence of ...
Working Paper
News-driven uncertainty fluctuations
We embed a news shock, a noisy indicator of the future state, in a two-state Markov-switching growth model. Our framework, combined with parameter learning, features rich history-dependent uncertainty dynamics. We show that bad news that arrives during a prolonged economic boom can trigger a ?Minsky moment??a sudden collapse in asset values. The effect is greatly amplified when agents have a preference for early resolution of uncertainty. We leverage survey recession probability forecasts to solve a sequential learning problem and estimate the full posterior distribution of model primitives. ...
Working Paper
Improving GDP measurement: a forecast combination perspective
Two often-divergent U.S. GDP estimates are available, a widely-used expenditure-side version GDPE, and a much less widely-used income-side version GDI . The authors propose and explore a "forecast combination" approach to combining them. They then put the theory to work, producing a superior combined estimate of GDP growth for the U.S., GDPC. The authors compare GDPC to GDPE and GDPI , with particular attention to behavior over the business cycle. They discuss several variations and extensions.
Working Paper
Identifying long-run risks: a bayesian mixed-frequency approach
We develop a nonlinear state-space model that captures the joint dynamics of consumption, dividend growth, and asset returns. Building on Bansal and Yaron (2004), our model consists of an economy containing a common predictable component for consumption and dividend growth and multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly consumption data after 1959, and monthly asset return data throughout. We maximize the span of the sample to recover the predictable component and use high-frequency data, whenever available, to ...
Working Paper
Real-time forecasting with a mixed-frequency VAR
This paper develops a vector autoregression (VAR) for macroeconomic time series which are observed at mixed frequencies ? quarterly and monthly. The mixed-frequency VAR is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. Using a real-time data set, we generate and evaluate forecasts from the mixed-frequency VAR and compare them to forecasts from a VAR that is estimated based on data time-aggregated to quarterly frequency. We document how information that becomes available within the quarter improves the forecasts in real time.