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Challenges in Nowcasting GDP Growth
Real gross domestic product (GDP) declined at an annualized rate of 4.8 percent in the first quarter, according to the first estimate from the U.S. Bureau of Economic Analysis (BEA), 3.8 percentage points more than the decline anticipated by the Atlanta Fed's final GDPNow model projection. Why was the error, which was easily the model's largest on record for final GDPNow forecasts, so big? Chart 1 looks at GDPNow's forecast errors since the model went live in mid-2014 and breaks them down into forecast errors for the various subcomponents' contributions to GDP growth.
Journal Article
The Phillips Curve during the Pandemic: Bringing Regional Data to Bear
The Phillips curve appears to have held up well at the regional level during the COVID-19 era. Areas of the country that took relatively large hits to their unemployment rate and employment-population ratio during the pandemic have had lower inflation, on average, than areas that took relatively small hits. And, just as prior to the pandemic, the inverse relationship between inflation and unemployment continues to be statistically stronger for the prices of services than of goods.
Journal Article
Industry-Level Sources for Solid US Employment Growth: Running on Empty or More Room to Run?
The labor market has exhibited solid growth in the past few years, largely due to the strong growth in three industries: Health Care and Social Assistance (HCSA), Leisure and Hospitality (LH), and Government (G). However, while the level of payroll employment surpassed prepandemic levels, a gap of approximately 3.4 million remains between these levels and the level of employment that would have been expected in the absence of the pandemic. Using data on vacancies and vacancy yields, we estimate that HCSA and G are quickly approaching their prepandemic trend trajectories. LH, however, is not ...
Working Paper
Assessing the Role of Global Demand and Supply Shocks in the Recent US Inflation Experience Using a Cross-Country Panel Dataset of Professional Forecasts
Although there have been a range of studies investigating the role and importance of global supply and demand shocks in US inflation developments during and since the pandemic, this study uses a heretofore unused dataset for this purpose: a quarterly panel of professional forecasts from Consensus Economics. We use real-time data with daily vintage snapshots since 2005 from the Federal Reserve Board of Governors FAME database to disentangle forecast errors from revisions and to exploit the monthly frequency and partial availability of CPI inflation and industrial production. Our measures of ...
Working Paper
Nowcasting with Mixed Frequency Principal Components When Not All Months Are the Same
This paper develops algorithms for estimating a principal components (PC) model for monthly macroeconomic data mixed with either weekly or daily data. The algorithms’ utilization of high frequency data allows it to account for differences in the temporal aggregation patterns among the monthly series that are simple aggregates or averages and those that have an alternative aggregation pattern such as data from the monthly employment report where the aggregation pattern is often series- and month-specific and depends on the timing of the twelfth day of the month. The algorithms are applied to ...
Working Paper
GDPNow: A Model for GDP "Nowcasting"
This paper documents GDPNow, a "nowcasting" model for gross domestic product (GDP) growth that synthesizes the "bridge equation" approach relating GDP subcomponents to monthly source data with the factor model approach used by Giannone, Reichlin, and Small (2008). The GDPNow model forecasts GDP growth by aggregating 13 subcomponents that make up GDP with the chain-weighting methodology used by the U.S. Bureau of Economic Analysis. Using current vintage data, out-of-sample GDPNow model forecasts are found to be more accurate than a number of statistical benchmarks since 2000. Using real-time ...
Working Paper
Forecasting China's Economic Growth and Inflation
Although macroeconomic forecasting forms an integral part of the policymaking process, there has been a serious lack of rigorous and systematic research in the evaluation of out-of-sample model-based forecasts of China's real gross domestic product (GDP) growth and consumer price index inflation. This paper fills this research gap by providing a replicable forecasting model that beats a host of other competing models when measured by root mean square errors, especially over long-run forecast horizons. The model is shown to be capable of predicting turning points and usable for policy analysis ...
Working Paper
Impacts of Monetary Stimulus on Credit Allocation and Macroeconomy: Evidence from China
We develop a new empirical framework to identify and estimate the effects of monetary stimulus on the real economy. The framework is applied to the Chinese economy when monetary policy in normal times was switched to an extraordinarily expansionary regime to combat the impact of the 2008 financial crisis. We show that this unprecedented monetary stimulus accounted for as high as a 4 percent increase of real gross domestic product (GDP) growth rate by the end of 2009. Monetary transmission to the real economy was through bank credit allocated disproportionately to financing investment in real ...
Working Paper
Did the 2017 Tax Reform Discriminate against Blue State Voters?
The Tax Cut and Jobs Act of 2017 (TCJA) made significant changes to corporate and personal federal income taxation, including limiting the SALT (state and local property, income and sales taxes) deductibility to $10,000. States with high SALT tend to vote Democratic. This paper estimates the differential effect of the TCJA on red- and blue-state taxpayers and investigates the importance of the SALT limitation to this differential. We calculate the effect of permanent implementation of the TCJA on households using The Fiscal Analyzer: a life-cycle, consumption-smoothing program incorporating ...
Working Paper
Cyclical Lending Standards: A Structural Analysis
Lending standards are a direct measure of credit conditions. We use the micro data merged from three separate sources to construct this measure and document that an uncertain macroeconomic outlook, rather than banks' balance sheet positions, was an important reason that a majority of banks tightened bank lending standards during the Great Recession. Our extensive data analysis disciplines how we introduce credit frictions in the banking sector into a macroeconomic model. The model estimation reveals that an exogenous shock to credit supply drives cyclical lending standards and accounts for a ...