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How Biased Are Measures Of Cyclical Movements In Productivity And Hours?


  • Stephanie Aaronson
  • Andrew Figura


The movement of hours worked over the business cycle is an important input into the estimation of many key parameters in macroeconomics. Unfortunately, the available data on hours do not correspond precisely to the concept required for accurate inference. We study one source of mismeasurement-that the most commonly used source data measure hours paid instead of hours worked. In particular, we focus our attention on salaried workers, a group for whom the gap between hours paid and hours worked is likely to be large. We show that the measurement gap varies significantly and positively with changes in labor demand. As a result, we estimate that the standard deviations of the workweek and of total hours worked are 27 and 5 percent larger, respectively, than published measures of hours suggest. We also find that this measurement gap is unlikely to be the source of the acceleration in published measures of productivity in the early 2000s. Copyright 2010 The Authors. Review of Income and Wealth 2010 International Association for Research in Income and Wealth.

Suggested Citation

  • Stephanie Aaronson & Andrew Figura, 2010. "How Biased Are Measures Of Cyclical Movements In Productivity And Hours?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(3), pages 539-558, September.
  • Handle: RePEc:bla:revinw:v:56:y:2010:i:3:p:539-558

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    References listed on IDEAS

    1. Ohlsson, Henry & Roine, Jesper & Waldenstrom, Daniel, 2006. "Long-Run Changes in the Concentration of Wealth: An Overview of Recent Findings," WIDER Working Paper Series 103, World Institute for Development Economic Research (UNU-WIDER).
    2. Facundo Alvaredo & Emmanuel Saez, 2009. "Income and Wealth Concentration in Spain from a Historical and Fiscal Perspective," Journal of the European Economic Association, MIT Press, vol. 7(5), pages 1140-1167, September.
    3. Gastwirth, Joseph L, 1972. "The Estimation of the Lorenz Curve and Gini Index," The Review of Economics and Statistics, MIT Press, vol. 54(3), pages 306-316, August.
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    Cited by:

    1. Andrew S. Green, 2017. "Hours Off the Clock," Working Papers 17-44, Center for Economic Studies, U.S. Census Bureau.
    2. Messinis, George, 2013. "Returns to education and urban-migrant wage differentials in China: IV quantile treatment effects," China Economic Review, Elsevier, vol. 26(C), pages 39-55.
    3. Jay Stewart, 2014. "The importance and challenges of measuring work hours," IZA World of Labor, Institute for the Study of Labor (IZA), pages 1-95, November.

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