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Interpreting aggregate wage growth

Author

Listed:
  • Richard Blundell

    (Institute for Fiscal Studies and University College London)

  • Howard Reed

    (Institute for Fiscal Studies)

  • Thomas M. Stoker

    (Institute for Fiscal Studies and MIT)

Abstract

This paper analyzes the relationship between aggregate wages and individual wages when there is time series variation in employment and in the dispersion of wages. A new and easily implementable framework for the empirical analysis of aggregation biases is developed. Aggregate real wages are shown to contain three important bias terms: one associated with the dispersion of individual wages, a second reflecting the distribution of working hours, and a third deriving from compositional changes in the (selected) sample of workers. Noting the importance of these issues for recent experience in Britain, data on real wages and participation for British male workers over the period 1978-1996 are studied. A close correspondence between the estimated biases and the patterns of differences shown by aggregate wages is established. This is shown to have important implications for the interpretation of real wage growth over this period.

Suggested Citation

  • Richard Blundell & Howard Reed & Thomas M. Stoker, 1999. "Interpreting aggregate wage growth," IFS Working Papers W99/13, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:ifsewp:99/13
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    File URL: http://www.ifs.org.uk/wps/wp9913.pdf
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    References listed on IDEAS

    as
    1. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
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    Cited by:

    1. Mirko Draca & Stephen Machin, 2015. "Crime and Economic Incentives," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 389-408, August.
    2. Peter Haan & Viktor Steiner, 2008. "Making Work Pay for the Elderly Unemployed - Evaluating Alternative Policy Reforms for Germany," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 64(3), pages 380-402, September.
    3. Guggenberger, Patrik & Smith, Richard J., 2008. "Generalized empirical likelihood tests in time series models with potential identification failure," Journal of Econometrics, Elsevier, vol. 142(1), pages 134-161, January.
    4. Michal Myck & Leszek Morawski & Jerzy Mycielski, 2006. "Employment Fluctuations and Dynamics of the Aggregate Average Wage in Poland 1996 - 2003," Discussion Papers of DIW Berlin 545, DIW Berlin, German Institute for Economic Research.
    5. P. Jenkins, Stephen, 2009. "Spaghetti unravelled: a model-based description of differences in income-age trajectories," ISER Working Paper Series 2009-30, Institute for Social and Economic Research.
    6. Anabela Carneiro & Pedro Portugal, 2004. "Workers' Flows and Real Wage Cyclicality," CEF.UP Working Papers 0402, Universidade do Porto, Faculdade de Economia do Porto.
    7. Pedro Carneiro & Sokbae (Simon) Lee, 2005. "Ability, sorting and wage inequality," CeMMAP working papers CWP16/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Heckman, James J. & Lochner, Lance J. & Todd, Petra E., 2006. "Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 7, pages 307-458, Elsevier.
    9. Richard Blundell & Amanda Gosling & Hidehiko Ichimura & Costas Meghir, 2007. "Changes in the Distribution of Male and Female Wages Accounting for Employment Composition Using Bounds," Econometrica, Econometric Society, vol. 75(2), pages 323-363, March.
    10. Michal Myck & Gillian Paull, 2001. "The role of employment experience in explaining the gender wage gap," IFS Working Papers W01/18, Institute for Fiscal Studies.
    11. Heckman, James J. & Masterov, Dimitriy V., 2004. "Skill Policies for Scotland," IZA Discussion Papers 1444, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Aggregate Real Earnings; Participation; Wage Distribution;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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