Abstract
Two often-divergent U.S. GDP estimates are available, a widely-used expenditure-side version GDPE, and a much less widely-used income-side version GDPI. We propose and explore a “forecast combination” approach to combining them. We then put the theory to work, producing a superior combined estimate of GDP growth for the U.S., GDPC. We compare GDPC to GDPE and GDPI, with particular attention to behavior over the business cycle. We discuss several variations and extensions.
Cite
CITATION STYLE
Aruoba, S. B., Diebold, F. X., Nalewaik, J., Schorfheide, F., & Song, D. (2013). Improving u.S. gdp measurement: A forecast combination perspective. In Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis: Essays in Honor of Halbert L. White Jr (pp. 1–25). Springer New York. https://doi.org/10.1007/978-1-4614-1653-1_1
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