Testing for Recent Trends in US Productivity Growth

Simon van Norden ()

No 177, Computing in Economics and Finance 2006 from Society for Computational Economics

Abstract: There is no shortage of opinions and discussion about recent productivity growth trends. In contrast, relatively little attention is paid to the degree of uncertainty surrounding recent estimates of such growth trends. This paper makes two contributions to the scant body of research that quantifies the precision with which such trends are estimated. It proposes a new test for recent breaks in trend when the breakpoint is not precisely known. The test is robust to departures from normality, reasonably sized in small samples, has the power to detect economically significant changes in productivity growth, and can be used to test for breakpoints with as little as a single observation. It examines the impact of data revision on the reliablity of tests for trend breaks using a new real-time data set for US Output per Person-Hour in the Non-Farm Business Sector recently made available by the St. Louis Federal Reserve Board. As noted by Arouba (2005), data revision in productivity data seems to be larger than in many other macroeconomic series (including output, inflation or unemployment.) We find that the failure to take account of the data revision process causes important distortions in tests for trend breaks

Keywords: real-time data; breaking trends; productivity growth (search for similar items in EconPapers)
JEL-codes: C22 E01 O47 (search for similar items in EconPapers)
Date: 2006-07-04
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecfa:177

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