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How Large are Long-run Revisions to Estimates of U.S. Labor Productivity Growth?

John Glaser, Peter B. Meyer, Jay Stewart, and Jerin Varghese


This paper examines long-term revisions to official estimates of quarterly US labor productivity growth, and to its components output and hours growth, for 2000-2015.  Estimates of output (GDP) and hours growth are revised substantially in the first months after the reference quarter.  The data continue to be revised long after the end of the reference quarter, although the magnitudes of the revisions are negligible after 5 years.  Revisions are due to the incorporation of additional microdata, benchmarking, adjustments to seasonal factors, and (for output) changes to definitions and methods—all of which are assumed to bring the estimates closer to “truth.” 

We find that revisions to output growth are substantially larger than revisions to hours growth and that the magnitude of revisions varies across reference quarters, with revisions being larger for Q1 and for recession quarters.  Long-term revisions to growth rates tend to be smaller than revisions to levels because revisions to current quarter and prior quarter levels tend to be in the same direction and of approximately the same magnitude.

Following earlier research, we estimate Mincer-Zarnowitz regressions to examine whether these long-term revisions are “news” and whether they eliminate “noise.”  We find that the initial revisions to output and hours are news, while later revisions are not.  Early revisions eliminate noise only for hours, while later revisions do not eliminate noise.  These findings seem to contradict the assumption that revisions bring estimates closer to the “true” value.  But further investigation resolves this apparent inconsistency.  We also examine the ability of the early estimates to “predict” estimate values after five years of revisions.