Nowcasting of advance estimates of personal consumption of Services in the U.S. National Economic Accounts: Individual vs forecasting combination approach
Corresponding Author
Baoline Chen
U.S. Bureau of Economic Analysis, BEA
Correspondence to: Baoline Chen and Kyle Hood, U.S. Bureau of Economic Analysis, BEA, Washington, DC, 20233, USA. Email: ([email protected]) and ([email protected])
Search for more papers by this authorCorresponding Author
Kyle Hood
U.S. Bureau of Economic Analysis, BEA
Correspondence to: Baoline Chen and Kyle Hood, U.S. Bureau of Economic Analysis, BEA, Washington, DC, 20233, USA. Email: ([email protected]) and ([email protected])
Search for more papers by this authorCorresponding Author
Baoline Chen
U.S. Bureau of Economic Analysis, BEA
Correspondence to: Baoline Chen and Kyle Hood, U.S. Bureau of Economic Analysis, BEA, Washington, DC, 20233, USA. Email: ([email protected]) and ([email protected])
Search for more papers by this authorCorresponding Author
Kyle Hood
U.S. Bureau of Economic Analysis, BEA
Correspondence to: Baoline Chen and Kyle Hood, U.S. Bureau of Economic Analysis, BEA, Washington, DC, 20233, USA. Email: ([email protected]) and ([email protected])
Search for more papers by this authorNote: We would like to thank the editor and an anonymous referee from Review of Income and Wealth, participants at the Joint Statistical Meetings of the American Economic Association (2021), the 40th International Symposium of Forecasts (2019), and the 62nd World Congress of the International Statistical Institute (2019) and Society for Economic Measurement (2018) for helpful comments, and Kyle Brown and Harvey Davis for their help with the data.
Abstract
As part of continuing effort to research statistical methods for producing timely and accurate early estimates of national accounts statistics, this paper evaluates the ability of individual nowcasting and forecast combination techniques to reduce revisions in the first or advance estimates of U.S. quarterly personal consumption of services at the most detailed component level. At such a level, designated indicators for advance estimates are those directly relevant to the detailed components. Using the same indicators that were used in routine compilations, we show in a real time setting that nowcasting methods are able to reduce revisions in the advance estimates in over 90 percent of the detailed components, and the upper bound of the reductions reached over 60 percent. We evaluate the performances of all methods by comparing their root mean squared revisions for each component. Our study suggests that nowcasting techniques are potentially a powerful tool to reduce revisions in the early estimates in the national account statistics at the most detailed level.
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