On the Sensitivity of Aggregate Productivity Growth Rates to Noisy Measurement
AbstractAggregate rates of productivity growth are among the most closely watched indicators of economic performance. They are also among the most difficult to measure accurately. This paper explores the sensitivity of such rates to random measurement error using a simple generic model. The model allows for errors in the input and output components of the productivity ratio, with different variances, and for serial and cross correlation of the errors. The effects of the errors are considered from the point of view of growth rates themselves, changes in growth rates, and comparisons between rates in different countries.
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Bibliographic InfoPaper provided by McMaster University in its series Social and Economic Dimensions of an Aging Population Research Papers with number 192.
Length: 24 pages
Date of creation: May 2007
Date of revision:
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More information through EDIRC
productivity; growth rates; measurement error;
Find related papers by JEL classification:
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
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- Michael C. Lovell, 1963. "Seasonal Adjustment of Economic Time Series and Multiple Regression," Cowles Foundation Discussion Papers 151, Cowles Foundation for Research in Economics, Yale University.
- Van Biesebroeck, Jo, 2004.
"Robustness of productivity estimates,"
Open Access publications from Katholieke Universiteit Leuven
urn:hdl:123456789/253800, Katholieke Universiteit Leuven.
- W. Erwin Diewert & Kevin J. Fox, 1999. "Can measurement error explain the productivity paradox?," Canadian Journal of Economics, Canadian Economics Association, vol. 32(2), pages 251-280, April.
- Baldwin, John R. Maynard, Jean-Pierre Tanguay, Marc Wong, Fanny Yan, Beiling, 2005. "A Comparison of Canadian and U.S. Productivity Levels: An Exploration of Measurement Issues," Economic Analysis (EA) Research Paper Series 2005028e, Statistics Canada, Analytical Studies Branch.
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