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The growth rate of real gross domestic product (GDP) is a key indicator of economic activity, but the official estimate is released with a delay. Our new GDPNow forecasting model provides a "nowcast" of the official estimate prior to its release. Recent forecasts for the GDPNow model are available here. More extensive numerical details—including underlying source data, forecasts, and model parameters—are available as a separate spreadsheet.

Latest forecast

The GDPNow model forecast for real GDP growth (seasonally adjusted annual rate) in the first quarter of 2015 was 0.2 percent on March 25, down from 0.3 percent on March 17. Following this morning's advance report on durable goods manufacturing from the U.S. Census Bureau, the nowcasts for real equipment investment and real inventory investment declined slightly.

Evolution of Atlanta Fed GDPNow Real GDP Forecast
  • Model Description

    The growth rate of real gross domestic product (GDP) measured by the U.S. Bureau of Economic Analysis (BEA) is a key metric of the pace of economic activity. It is one of the four variables included in the economic projections of Federal Reserve Board members and Bank presidents for every other Federal Open Market Committee (FOMC) meeting. As with many economic statistics, GDP estimates are released with a lag whose timing can be important for policymakers. For example, of the four scheduled 2014 release dates of an “advance” (or first) estimate of GDP growth, two are on the second day of a scheduled FOMC meeting with the other two on the day after the meeting. In preparation for FOMC meetings, policymakers have the Fed Board staff projection of this “advance” estimate at their disposal. These projections—available through 2008 at the Philadelphia Fed’s Real Time Data Center—have generally been more accurate than forecasts from simple statistical models. As stated by economists Jon Faust and Jonathan H. Wright in a 2009 paper, “by mirroring key elements of the data construction machinery of the Bureau of Economic Analysis, the Fed staff forms a relatively precise estimate of what BEA will announce for the previous quarter’s GDP even before it is announced.”

    The Atlanta Fed GDPNow model also mimics the methods used by the BEA to estimate real GDP growth. The GDPNow forecast is constructed by aggregating statistical model forecasts of 13 subcomponents that comprise GDP. Other private forecasters use similar approaches to “nowcast” GDP growth. However, these forecasts are not updated more than once a month or quarter, are not publicly available, or do not have forecasts of the subcomponents of GDP that add “color” to the top-line number. The Atlanta Fed GDPNow model fills these three voids.

    The BEA’s advance estimates of the subcomponents of GDP use publicly released data from the U.S. Census Bureau, U.S. Bureau of Labor Statistics, and other sources. Much of this data is displayed in the BEA’s Key Source Data and Assumptions table that accompanies the “advance” GDP estimate. GDPNow relates these source data to their corresponding GDP subcomponents using a “bridge equation” approach similar to the one described in a Minneapolis Fed study by Preston J. Miller and Daniel M. Chin. Whenever the monthly source data is not available, the missing values are forecasted using econometric techniques similar to those described in papers by James H. Stock and Mark W. Watson and Domenico Giannone, Lucrezia Reichlin, and David Small. A detailed description of the data sources and methods used in the GDPNow model is provided in an accompanying Atlanta Fed working paper.

    As more monthly source data becomes available, the GDPNow forecast for a particular quarter evolves and generally becomes more accurate. That said, the forecasting error can still be substantial just prior to the “advance” GDP estimate release. It is important to emphasize that the Atlanta Fed GDPNow forecast is a model projection not subject to judgmental adjustments. It is not an official forecast of the Federal Reserve Bank of Atlanta, its president, the Federal Reserve System, or the FOMC.

    ©2015 Federal Reserve Bank of Atlanta. All rights reserved. Permission is granted to reproduce for personal and educational use only.

  • Frequently Asked Questions

    Is GDPNow an official forecast of the Atlanta Fed or the Bank’s president?
    No, it is not an official forecast of the Atlanta Fed, its president, the Federal Reserve System, or the FOMC.

    Is any judgment used to adjust the forecasts?
    No. Once the GDPNow model begins forecasting GDP growth for a particular quarter, the code will not be adjusted until after the “advance” estimate. If we improve the model over time, we will roll out changes right after the “advance” estimate so that forecasts for the subsequent quarter use a fixed methodology for their entire evolution.

    When will forecasts of GDP growth in a particular quarter start being made?
    About 90 days before the “advance” estimate for GDP growth for the quarter is released. GDPNow forecasts begin the weekday after the BEA’s “advance” estimate of GDP growth for the previous quarter is released. For example, the advance estimate of real GDP growth in the fourth quarter of 2013 was released on January 30, 2014. The GDPNow forecasts for real GDP growth in the first quarter of 2014 were tracked from January 31, 2014, until the day before the “advance” estimate released on April 30, 2014.

    How frequently is the GDPNow forecast updated?
    The model forecast is updated five or six times a month on weekdays, with at least one following six data releases: Manufacturing ISM Report on Business, U.S. International Trade in Goods and Services (FT900), Monthly Retail Trade Report, New Residential Construction, Advance Report on Durable Goods Manufacturers, and Personal Income and Outlays. Other data releases, such as Wholesale Trade and Existing-Home Sales, are incorporated in the model as well and their impact on the model’s forecast will be shown on the weekday after one of the six data releases. The proprietary forecasts from Blue Chip Economic Indicators and Blue Chip Financial Forecasts shown in the chart are available from Aspen Publishers.

    Where can I read about the methods and source data used in the model?
    A detailed description is given in a working paper describing the model. To summarize, the BEA’s NIPA Handbook provides very detailed documentation on both the source data and methods used for estimating the subcomponents of GDP. The late Nobel Prize–winning economist Lawrence Klein pioneered many of the “bridge equation” methods used for making short-run forecasts of GDP growth using this source data; a 1989 paper he coauthored with E. Sojo describes the approach. Ben Herzon, an economist at Macroeconomic Advisers, provides a bird’s-eye view illustrating how to use a bridge equation approach in practice to improve GDP forecasts in this 2013 presentation. The econometric techniques used in our GDPNow model were heavily adapted from the GDP nowcasting models described in a 1996 Minneapolis Fed Quarterly Review article by Preston J. Miller and Daniel M. Chin and a 2008 paper by the Board’s David Small and economists Domenico Giannone and Lucrezia Reichlin.

    Where can I find alternative forecasts of GDP growth?
    For model forecasts from other Fed Banks, see the Minneapolis Mixed Frequency Vector Autoregression (MF-VAR) model, the Philadelphia Research Intertemporal Stochastic Model (PRISM), and the Federal Reserve Bank of Cleveland’s prediction model for GDP growth based on the slope of the yield curve. Moody’s Analytics and produce proprietary model short-run GDP forecasts. For survey-based forecasts, see the Philadelphia Fed’s quarterly Survey of Professional Forecasters, which includes forecasts of real GDP and its major subcomponents. The Wall Street Journal’s Economic Forecasting Survey occurs monthly but does not include forecasts of the subcomponents of GDP.

    How accurate are the GDPNow forecasts? Are they more accurate than “professional” forecasts?
    Since we started tracking GDP growth with versions of this model in 2011, the average absolute error of the model’s real-time forecast made just prior to the release of the “advance” (first) estimate of the annualized growth rate of real GDP is 0.68 percentage point. The root-mean-squared error of the forecasts has been 0.94 percentage point. These accuracy measures cover “advance” estimates for 2011Q3–2014Q1. We have made some improvements to the model from its earlier versions and the model forecasts have become more accurate over time (the complete track record is here). When back-testing with revised data, the root mean-squared error of the model’s out-of sample forecast with the same data coverage that an analyst would have just before the “advance” estimate is 1.15 percentage points for the 2000q1–2013q4 period. The figure below shows how the forecasts become more accurate as the interval between the date the forecast is made and the forthcoming GDP release date narrows.

    Root Mean Square Forecast Error of GDP Growth (SAAR) for GDPNow Model

    Overall, these accuracy metrics do not give compelling evidence that the model is more accurate than professional forecasters. The model does appear to fare well compared to other conventional statistical models.

    How are revisions to data not yet reflected in the latest GDP release handled?
    In general, the model does not attempt to anticipate how data releases after the latest GDP report will affect the revisions made in the forthcoming GDP release. The exception is the “change in private inventories” subcomponent, where revisions to the prior quarter reading affect GDP growth in the current quarter. Users of the GDPNow forecast should generally use the forecasts of the change in “net exports” and the change in the “change in private inventories,” and not forecasts of the levels. Revisions to retail sales are used to anticipate revisions to real monthly expenditures in the “PCE control group” and revisions to housing starts are used to anticipate revisions in the monthly value of private residential construction spending put in place.

    Do you share your code?
    At this point, no. However, the Excel spreadsheet gives the numerical details—including the raw data and model parameters—of how the monthly data map into forecasts of the subcomponents of GDP.

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