IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-319-48454-9_28.html
   My bibliography  Save this book chapter

Are We Better Off Working in the Public Sector?

In: Advances in Applied Economic Research

Author

Listed:
  • Yi Wang

    (Cardiff School of Management, Cardiff Metropolitan University)

  • Peng Zhou

    (Cardiff Business School, Cardiff University)

Abstract

This paper critically reviews the literature on public sector wage premium, especially in the developed countries like the USA and the UK. It is found that the pay advantage is persistent over the latest half century, but it started to decline since the late-1990s; in particular, females tend to enjoy a higher wage premium than males. A key technical problem of estimating wage premium is selection bias, because the sector choice is endogenously determined by individual characteristics and job attributes. The main prevailing methods in the current literature are categorised into four main types, and a sample dataset from the Labour Force Survey (UK) in the latest decade is used to apply and compare these methods. The findings suggest that Blinder–Oaxaca and OLS seem to underestimate the wage premium by 2 %, compared to propensity score matching method.

Suggested Citation

  • Yi Wang & Peng Zhou, 2017. "Are We Better Off Working in the Public Sector?," Springer Proceedings in Business and Economics, in: Nicholas Tsounis & Aspasia Vlachvei (ed.), Advances in Applied Economic Research, chapter 0, pages 379-409, Springer.
    • Handle: RePEc:spr:prbchp:978-3-319-48454-9_28
    DOI: 10.1007/978-3-319-48454-9_28
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Keywords

    Public sector wage premium; Decomposition; Treatment effect; Propensity score matching;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J45 - Labor and Demographic Economics - - Particular Labor Markets - - - Public Sector Labor Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:prbchp:978-3-319-48454-9_28. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.