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Forecasting GDP Growth with NIPA Aggregates

Author

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  • Christian Garciga
  • Edward S. Knotek

Abstract

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 time-series models have historically generated more accurate forecasts than a canonical AR(2) benchmark. This has been especially true during recessions, although we document modest gains during expansions as well.

Suggested Citation

  • Christian Garciga & Edward S. Knotek, 2017. "Forecasting GDP Growth with NIPA Aggregates," Working Papers (Old Series) 1708, Federal Reserve Bank of Cleveland.
    • Handle: RePEc:fip:fedcwp:1708
    DOI: 10.26509/frbc-wp-201708
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    More about this item

    Keywords

    forecasting; GDP; GDI; real-time data; consumption;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

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