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Working Paper
Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy
This paper constructs hybrid forecasts that combine both short- and long-term conditioning information from external surveys with forecasts from a standard fixed-coefficient vector autoregression (VAR) model. Specifically, we use relative entropy to tilt one-step ahead and long-horizon VAR forecasts to match the nowcast and long-horizon forecast from the Survey of Professional Forecasters. The results indicate meaningful gains in multi-horizon forecast accuracy relative to model forecasts that do not incorporate long-term survey conditions. The accuracy gains are achieved for a range of ...
Working Paper
Nowcasting U.S. Headline and Core Inflation
Forecasting future inflation and nowcasting contemporaneous inflation are difficult. We propose a new and parsimonious model for nowcasting headline and core inflation in the U.S. price index for personal consumption expenditures (PCE) and the consumer price index (CPI). The model relies on relatively few variables and is tested using real-time data. The model?s nowcasting accuracy improves as information accumulates over the course of a month or quarter, and it easily outperforms a variety of statistical benchmarks. In head-to-head comparisons, the model?s nowcasts of CPI infl ation ...
Working Paper
Frequency Dependence in a Real-Time Monetary Policy Rule
We estimate a monetary policy rule for the US allowing for possible frequency dependence?i.e., allowing the central bank to respond differently to more persistent innovations than to more transitory innovations, in both the unemployment rate and the inflation rate. Our estimation method uses real-time data in these rates?as did the FOMC?and requires no a priori assumptions on the pattern of frequency dependence or on the nature of the processes generating either the data or the natural rate of unemployment. Unlike other approaches, our estimation method allows for possible feedback in the ...
Working Paper
Forecasting GDP Growth with NIPA Aggregates
Beyond GDP, which is measured using expenditure data, the U.S. national income and product accounts (NIPAs) provide an income-based measure of the economy (gross domestic income, or GDI), a measure that averages GDP and GDI, and various aggregates that include combinations of GDP components. This paper compiles real-time data on a variety of NIPA aggregates and uses these in simple time-series models to construct out-of-sample forecasts for GDP growth. Over short forecast horizons, NIPA aggregates?particularly consumption and GDP less inventories and trade?together with these simple ...
Working Paper
Nowcasting Inflation
This chapter summarizes the mixed-frequency methods commonly used for nowcasting inflation. It discusses the importance of key high-frequency data in producing timely and accurate inflation nowcasts. In the US, consensus surveys of professional forecasters have historically provided an accurate benchmark for inflation nowcasts because they incorporate professional judgment to capture idiosyncratic factors driving inflation. Using real-time data, we show that a relatively parsimonious mixed-frequency model produces superior point and density nowcasting accuracy for headline inflation and ...
Working Paper
Are Revisions to State-Level GDP Data in the US Well Behaved?
No, first estimates of state GDP growth are not rational forecasts, except for Georgia. Revisions to first estimates of state-level GDP growth tend to be biased, large, and/or predictable using information known at the time of the first estimate.
Working Paper
Two Measures of Core Inflation: A Comparison
Trimmed-mean Personal Consumption Expenditure (PCE) inflation does not clearly dominate ex-food-and-energy PCE inflation in real-time forecasting of headline PCE inflation. However, trimmed-mean inflation is the superior communications and policy tool because it is a less-biased real-time estimator of headline inflation and because it more successfully filters out headline inflation?s transitory variation, leaving only cyclical and trend components.
Working Paper
The Labor Market Impact of a Pandemic: Validation and Application of a Do-It-Yourself CPS
The Current Population Survey (CPS) is a central source of U.S. labor market data. We show that, for a few thousand dollars, researchers can quickly design and implement their own online survey to supplement the CPS. The survey closely follows core features of the CPS, ensuring that outcomes are conceptually compatible and allowing researchers to weight and validate results using the official CPS. Yet the survey also allows for faster data collection, added flexibility and novel questions. We show that the survey provided useful estimates of U.S. labor market aggregates several weeks ahead of ...
Working Paper
The Accuracy of Forecasts Prepared for the Federal Open Market Committee
We analyze forecasts of consumption, nonresidential investment, residential investment, government spending, exports, imports, inventories, gross domestic product, inflation, and unemployment prepared by the staff of the Board of Governors of the Federal Reserve System for meetings of the Federal Open Market Committee from 1997 to 2008, called the Greenbooks. We compare the root mean squared error, mean absolute error, and the proportion of directional errors of Greenbook forecasts of these macroeconomic indicators to the errors from three forecasting benchmarks: a random walk, a first-order ...
Working Paper
Out-of-Sample Inference with Annual Benchmark Revisions
This paper examines the properties of out-of-sample predictability tests evaluated with real-time data subject to annual benchmark revisions. The presence of both regular and annual revisions can create time heterogeneity in the moments of the real-time forecast evaluation function, which is not compatible with the standard covariance stationarity assumption used to derive the asymptotic theory of these tests. To cover both regular and annual revisions, we replace this standard assumption with a periodic covariance stationarity assumption that allows for periodic patterns of time ...