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The Structure of the Wage Gap for Temporary Workers: Evidence from Australian Panel Data

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  • Inga Laß
  • Mark Wooden

Abstract

This study uses panel data for Australia to estimate the wage differential between workers in temporary jobs and workers in permanent jobs. It is the first study to use unconditional quantile regression methods in combination with fixed effects to examine how this gap varies over the entire wage distribution. While the wages of fixed‐term contract workers are found to be similar to those of permanent workers, low‐paid casual workers experience a wage penalty and high‐paid casual workers a wage premium compared to their permanent counterparts. Temporary agency workers also usually receive a wage premium, which is particularly large for the most well paid.

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  • Inga Laß & Mark Wooden, 2019. "The Structure of the Wage Gap for Temporary Workers: Evidence from Australian Panel Data," British Journal of Industrial Relations, London School of Economics, vol. 57(3), pages 453-478, September.
    • Handle: RePEc:bla:brjirl:v:57:y:2019:i:3:p:453-478
    DOI: 10.1111/bjir.12458
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    Cited by:

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    2. Kamal, Mustafa & Blacklow, Paul, 2021. "Australian age, period, cohort effects in the gender wage gap - 2001 to 2018," Working Papers 2021-02, University of Tasmania, Tasmanian School of Business and Economics.
    3. Thanh Tam Nguyen-Huu, 2023. "Wage Inequality in Pakistan: How Does Contract Status Matter?," Post-Print hal-04248144, HAL.
    4. Duman, Anil, 2020. "Non-Standard Employment and Wage Differences across Gender: a quantile regression approach," GLO Discussion Paper Series 664, Global Labor Organization (GLO).
    5. Aalia Cassim & Daniela Casale, 2018. "How large is the wage penalty in the labour broker sector?: Evidence for South Africa using administrative data," WIDER Working Paper Series wp-2018-48, World Institute for Development Economic Research (UNU-WIDER).
    6. Paolo Barbieri & Giorgio Cutuli, 2018. "Dual Labour Market Intermediaries in Italy: How to Lay off “Lemons”—Thereby Creating a Problem of Adverse Selection," De Economist, Springer, vol. 166(4), pages 477-502, December.
    7. Albanese, Andrea & Gallo, Giovanni, 2020. "Buy flexible, pay more: The role of temporary contracts on wage inequality," Labour Economics, Elsevier, vol. 64(C).
    8. Egidio Farina & Colin Green & Duncan McVicar, 2020. "Zero Hours Contracts and Their Growth," British Journal of Industrial Relations, London School of Economics, vol. 58(3), pages 507-531, September.
    9. Daniela Casale & Aalia Cassim, 2018. "How large is the wage penalty in the labour broker sector?: Evidence for South Africa using administrative data," WIDER Working Paper Series 48, World Institute for Development Economic Research (UNU-WIDER).
    10. Garcia-Louzao, Jose & Hospido, Laura & Ruggieri, Alessandro, 2023. "Dual returns to experience," Labour Economics, Elsevier, vol. 80(C).
    11. Ivan Lagrosa, 2022. "Income dynamics in dual labor markets," Working Papers wp2022_2209, CEMFI.
    12. Egidio Farina & Colin Green & Duncan McVicar, 2021. "Are Estimates of Non‐Standard Employment Wage Penalties Robust to Different Wage Measures? The Case of Zero‐hour Contracts in the UK," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 60(3), pages 370-399, July.
    13. Marek Gora & Piotr Lewandowski & Maciej Lis, 2017. "Temporary employment boom in Poland – a job quality vs. quantity trade-off?," IBS Working Papers 04/2017, Instytut Badan Strukturalnych.
    14. Christine ABLAZA & Mark WESTERN & Wojtek TOMASZEWSKI, 2021. "Good jobs and bad jobs for Indonesia's informal workers," International Labour Review, International Labour Organization, vol. 160(1), pages 143-168, March.
    15. Inga Laß & Thomas Skora & Heiko Rüger & Mark Wooden & Martin Bujard, 2024. "Does temporary employment increase length of commuting? Longitudinal evidence from Australia and Germany," Transportation, Springer, vol. 51(4), pages 1467-1491, August.
    16. Geoff Weir, 2018. "Wage Growth Puzzles and Technology," RBA Research Discussion Papers rdp2018-10, Reserve Bank of Australia.
    17. Inga Laß & Mark Wooden, 2020. "Non‐Standard Employment and Wage Growth in Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 53(3), pages 325-342, September.
    18. Bill Cochrane & Gail Pacheco & Chao Li, 2017. "Temporary-Permanent Wage Gap: Does Type of Work and Location in Distribution Matter?," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 20(2), pages 125-147.
    19. Oliver Alexander & Jeff Borland & Andrew Charlton & Amit Singh, 2022. "The Labour Market for Uber Drivers in Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 55(2), pages 177-194, June.
    20. Alessia Matano, 2022. "Spatial externalities in big cities and duality of the labour market," Journal of Regional Science, Wiley Blackwell, vol. 62(2), pages 471-498, March.
    21. Mark Wooden, 2021. "Job Characteristics and the Changing Nature of Work," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 54(4), pages 494-505, December.
    22. Kapoor Radhicka & Krishnapriya P. P., 2023. "Informalization of the formal sector: Evidence from India's manufacturing industries," IZA Journal of Development and Migration, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 14(1), pages 1-29, January.

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    More about this item

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J41 - Labor and Demographic Economics - - Particular Labor Markets - - - Labor Contracts
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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