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The Importance of Skill Measurement for Growth Accounting

Author

Listed:
  • Nilsen, Øivind Anti

    (Norwegian School of Economics)

  • Raknerud, Arvid

    (Statistics Norway)

  • Rybalka, Marina

    (Statistics Norway)

  • Skjerpen, Terje

    (Statistics Norway)

Abstract

In a growth accounting context one usually constructs a quality adjusted index of labor services by aggregating over predefined groups of workers, using the groups' relative wage bills as weights. In this article we suggest a method based on decomposing individual predicted wages into a skill-related part and a part unrelated to skill, where the former consists of both observed and unobserved components. The predicted wages, associated with individual skill attributes, are sorted and classified into deciles. The median predicted skill-related wage in each decile is used to construct an alternative skill-adjusted index of labor services. We find that Total Factor Productivity (TFP) growth decreases significantly when using the latter method. This means that when using the alternative method one explains more of the growth in labor productivity than what a more traditional labor quality adjustment procedure does.

Suggested Citation

  • Nilsen, Øivind Anti & Raknerud, Arvid & Rybalka, Marina & Skjerpen, Terje, 2010. "The Importance of Skill Measurement for Growth Accounting," IZA Discussion Papers 4997, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp4997
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    References listed on IDEAS

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    Cited by:

    1. Thomas von Brasch & Ådne Cappelen & Diana-Cristina Iancu, 2015. "Understanding the productivity slowdown. The importance of entry and exit of workers," Discussion Papers 818, Statistics Norway, Research Department.
    2. Paul E. Brockway & Harry Saunders & Matthew K. Heun & Timothy J. Foxon & Julia K. Steinberger & John R. Barrett & Steve Sorrell, 2017. "Energy Rebound as a Potential Threat to a Low-Carbon Future: Findings from a New Exergy-Based National-Level Rebound Approach," Energies, MDPI, vol. 10(1), pages 1-24, January.
    3. Golombek, Rolf & Raknerud, Arvid, 2018. "Exit dynamics of start-up firms: Structural estimation using indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 204-225.
    4. Thomas von Brasch & Ådne Cappelen & Diana‐Cristina Iancu, 2018. "Measuring Labour Services: Quality‐Adjusting the Entry and Exit of Workers," Scandinavian Journal of Economics, Wiley Blackwell, vol. 120(2), pages 597-623, April.
    5. Mateusz Pipien & Sylwia Roszkowska, 2015. "Returns to skills in Europe – same or different? The empirical importance of the systems of regressions approach," NBP Working Papers 226, Narodowy Bank Polski.
    6. Paul E. Brockway & Matthew K. Heun & João Santos & John R. Barrett, 2017. "Energy-Extended CES Aggregate Production: Current Aspects of Their Specification and Econometric Estimation," Energies, MDPI, vol. 10(2), pages 1-23, February.
    7. Mateusz Pipień & Sylwia Roszkowska, 2018. "Returns to skills and work experience in Europe. Same or different?," Bank i Kredyt, Narodowy Bank Polski, vol. 49(5), pages 433-460.

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    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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