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Staff engagement, coworkers’ complementarity and employee retention: Evidence from English NHS hospitals

Author

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  • Moscelli, G.;
  • Sayli, M.;
  • Mello, M.;

Abstract

Retention of skilled workers is essential for labour-intensive organisations like hospitals, where an excessive turnover of doctors and nurses can reduce the quality and quantity of services to patients. In the public sector, where salaries are often not negotiable at individual level, workers increasingly care about the non-pecuniary aspects of their jobs. We empirically investigate the role played by two such aspects, staff engagement and the retention of complementary coworkers, in affecting employee retention within the public hospital sector. We exploit a unique and rich panel dataset based on employee-level payroll and staff survey records from the universe of English NHS hospitals, and estimate dynamic panel data models to deal with the bias due to reverse causality. We find that nurses’ retention is positively associated with their engagement, whereas doctors’ retention is positively associated with nurses’ retention. This heterogeneous response of employee retention can be explained by the hierarchy of workers’ professional roles within the organisation.

Suggested Citation

  • Moscelli, G.; & Sayli, M.; & Mello, M.;, 2022. "Staff engagement, coworkers’ complementarity and employee retention: Evidence from English NHS hospitals," Health, Econometrics and Data Group (HEDG) Working Papers 22/25, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:22/25
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    Cited by:

    1. Paola Bertoli & Veronica Grembi, 2025. "The Great Escape: Physicians Leaving the Public Sector," BAFFI CAREFIN Working Papers 25243, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    2. Costi, Chiara & Clark, Andrew E. & Lepinteur, Anthony & D'Ambrosio, Conchita, 2023. "Healthcare Workers and Life Satisfaction during the Pandemic," IZA Discussion Papers 16680, Institute of Labor Economics (IZA).

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    Keywords

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    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J28 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Safety; Job Satisfaction; Related Public Policy
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

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