Search Results
Journal Article
Forecasting US Recessions in Real-Time Using Regional Economic Sentiment
Measures of regional economic sentiment, extracted from the Beige Book using natural language processing methods, consistently delivered reliable real-time forecasts of US recessions from the mid-1980s through the COVID-19 pandemic recession. Since then, recession risk probabilities have been choppy, with several false alarms. We attribute this unreliability to a post-2021 disconnect between measures of economic activity and the sentiment of business and community leaders.
Journal Article
A New Measure of Consumers’ (In)Attention to Inflation
Since the onset of the SARS-CoV-2 (COVID-19) pandemic in March 2020, the Federal Reserve Bank of Cleveland has been running a daily survey that asks consumers for their views on how they are responding to COVID-19 and how COVID-19 is likely to affect the economy. Among the many questions asked, the survey solicits consumers’ inflation expectations. This is an important data set given that such expectations, while affected by current and past inflation, have long been believed to influence future inflation. In this Commentary, we use these daily expectations data to propose a new measure of ...
Journal Article
Regional Economic Sentiment: Constructing Quantitative Estimates from the Beige Book and Testing Their Ability to Forecast Recessions
We use natural language processing methods to quantify the sentiment expressed in the Federal Reserve's anecdotal summaries of current economic conditions in the national and 12 Federal Reserve District-level economies as published eight times per year in the Beige Book since 1970. We document that both national and District-level economic sentiment tend to rise and fall with the US business cycle. But economic sentiment is extremely heterogeneous across Districts, and we find that national economic sentiment is not always the simple aggregation of District-level sentiment. We show that the ...
Working Paper
Incorporating Micro Data into Macro Models Using Pseudo VARs
This paper develops a method to incorporate micro data, available as repeated cross-sections, into macro VAR models to understand the distributional effects of macroeconomic shocks at business cycle frequencies. The method extends existing functional VAR models by "looking within" the micro distribution to identify the degree to which specific types of micro units are affected by macro shocks. It does so by creating a pseudo-panel from the repeated cross-section and adding these pseudo individuals into the macro VAR. Jointly modeling the micro and macro data leads to a large (pseudo) VAR, and ...
Working Paper
The Causal Effects of Tariff Uncertainty on Consumers' Macroeconomic Expectations and Spending Plans
We use a large-scale randomized controlled trial to study the causal effects of tariff beliefs on US consumers' macroeconomic expectations and spending plans. We find that it is important to distinguish between the first- and second-moment effects of tariff rate changes. Exogenous variation in tariff-level expectations and perceived future tariff uncertainty differentially affects consumers' expectations and perceived uncertainty about inflation, GDP growth, and unemployment. Furthermore, higher expectations of tariff rates induce an intertemporal substitution effect, increasing consumers' ...
Working Paper
Consumers' Attention to Monetary Policy: The Importance of Having "Skin in the Game"
Using a five-year survey of over 170,000 US consumers, we provide a novel direct measure of attention to monetary policy and show that the data strongly support the predictions of a rational inattention model. First, attention is incentive-driven: consumers with "skin in the game"—those planning major purchases like homes or cars—are significantly more attentive to monetary policy news. Second, attention varies systematically with interest rate volatility and news supply, exhibiting cyclical patterns around FOMC meetings. Third, marginal effects of volatility and news supply decline with ...
Working Paper
Censored Density Forecasts: Production and Evaluation
This paper develops methods for the production and evaluation of censored density forecasts. The focus is on censored density forecasts that quantify forecast risks in a middle region of the density covering a specified probability, and ignore the magnitude but not the frequency of outlying observations. We propose a fixed-point algorithm that fits a potentially skewed and fat-tailed density to the inner observations, acknowledging that the outlying observations may be drawn from a different but unknown distribution. We also introduce a new test for calibration of censored density forecasts. ...
Working Paper
Censored Density Forecasts: Production and Evaluation
This paper develops methods for the production and evaluation of censored density forecasts. Censored density forecasts quantify forecast risks in a middle region of the density covering a specified probability, and ignore the magnitude but not the frequency of outlying observations. We propose a new estimator that fits a potentially skewed and fat-tailed density to the inner observations, acknowledging that the outlying observations may be drawn from a different but unknown distribution. We also introduce a new test for calibration of censored density forecasts. An application using ...
Working Paper
Communicating Data Uncertainty: Multi-Wave Experimental Evidence for UK GDP
Economic statistics are commonly published without estimates of their uncertainty. We conduct two waves of a randomized controlled online experiment to assess if and how the UK public understands data uncertainty. A control group observes only the point estimate of GDP. Treatment groups are presented with alternative qualitative and quantitative communications of GDP data uncertainty. We find that most of the public understands that GDP numbers are uncertain. Quantitative communications of data uncertainty help align the public’s subjective probabilistic expectations of data uncertainty ...
Working Paper
Communicating Data Uncertainty: Multi-Wave Experimental Evidence for UK GDP
Economic statistics are commonly published without any explicit indication of their uncertainty. To assess if and how the UK public interprets and understands data uncertainty, we conduct two waves of a randomized controlled online experiment. A control group is presented with the headline point estimate of GDP, as emphasized by the statistical office. Treatment groups are then presented with alternative qualitative and quantitative communications of GDP data uncertainty. We find that most of the public understands that uncertainty is inherent in official GDP numbers. But communicating ...