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Forecasting GDP Growth with NIPA Aggregates

Christian Garciga () and Edward Knotek ()

No 1708, Working Papers (Old Series) from Federal Reserve Bank of Cleveland

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.

Keywords: GDP; real-time data; consumption; GDI; forecasting (search for similar items in EconPapers)
JEL-codes: C32 C53 E01 (search for similar items in EconPapers)
Pages: 54 pages
Date: 2017-05-19, Revised 2017-05-19
New Economics Papers: this item is included in nep-dcm, nep-for and nep-mac
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DOI: 10.26509/frbc-wp-201708

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