Federal Reserve Bank of Cleveland
Working Papers (Old Series)
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 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.
Cite this item
Edward S. Knotek & Christian Garciga, Forecasting GDP Growth with NIPA Aggregates, Federal Reserve Bank of Cleveland, Working Papers (Old Series) 1708, 19 May 2017.
- 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
Keywords: forecasting; GDP; GDI; real-time data; consumption
This item with handle RePEc:fip:fedcwp:1708
is also listed on EconPapers
For corrections, contact 4D Library ()