Improving GDP Measurement: A Forecast Combination Perspective

Working Paper: NBER ID: w17421

Authors: S. Boragan Aruoba; Francis X. Diebold; Jeremy Nalewaik; Frank Schorfheide; Dongho Song

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.

Keywords: GDP Measurement; Forecast Combination; Economic Growth

JEL Codes: E01; E32


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
GDPE and GDPI (E20)GDPC (O49)
GDPE (D58)True GDP (E20)
GDPI (E20)True GDP (E20)
GDPE and GDPI errors (C82)GDPC (O49)

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