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The Economics of Presenteeism: A discrete choice & count model framework

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Abstract

There are three levels in this paper: A search for economic theories about presenteeism, a search for appropriate econometric approaches, and finally empirical results based on a unique Danish cross sectional data set. There are two economic approaches to presenteeism: 1. Productivity losses and 2. labor supply. The first is part of the indirect cost component in cost-of-illness studies and economic evaluation. There are two core questions in the productivity loss literature: Measurement of productivity losses (‘how much’) which has dominated the research agenda and valuation of incurred productivity losses (monetary value). Few economists have addressed the valuation issue and point out that the wage rate sometimes is inadequate. The starting point in the labor supply literature is sickness absence coupled with labor demand. The few economic models about presenteeism are explored and found lacking in the sense that they do not capture the essence of presenteeism. However, discrete choice models (random utility models) seem to be adequate in that the choice about going sick to work basically is a discrete choice situation that can be extended to include discrete counts, i.e. episodes of presenteeism within a given time period. The econometrics of presenteeism must have count models as the starting point due to the many zeroes, i.e. many persons do not experience presenteeism and, if they do, usually relatively few days (‘events’) in a given period and the discrete choice nature of presenteeism. Drawing on the econometric literature on utilization of medical services, the following models are discussed briefly: Poisson models, negative binominal, zero-inflated negative binomial, two part models (hurdle models) and latent class models (finite mixture models). This is in contrast to almost all previous literature where logistic regression has been the dominant statistical strategy. The Poissson model is discarded because an important feature (mean – variance) does not hold. The other models are all used in the empirical part of the paper, and an attempt at model selection is made. The empirical analyses are based on a cross-section survey of Danes in the labor force, N=4,060. The survey was designed with presenteeism in mind – one of the few available data sets at present. Ideally, theory/models should guide empirical work, but can do so only if fully specified theories are available and this is not the case for the random utility models that do no provide much guidance on relevant explanatory variables. The explanatory variables therefore are selected from the existing empirical works along with a number of new variables used in the survey, e.g. attitudinal variables about presenteeism and sickness absence and questions about work environment. A consistent result across all analyses is – not surprisingly - the importance of self reported health status: The worse health situation, the more presenteeism. . Another consistent result is that sickness absence and presenteeism are positively correlated. Persons with managerial positions also consistently have more presenteeism Age and genders are also (almost) consistently statistically significant. Fear of unemployment is also consistently and significantly related to presenteeism.

Suggested Citation

  • Pedersen, Kjeld Møller & Skagen, Kristian, 2014. "The Economics of Presenteeism: A discrete choice & count model framework," COHERE Working Paper 2014:2, University of Southern Denmark, COHERE - Centre of Health Economics Research.
  • Handle: RePEc:hhs:sduhec:2014_002
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    Cited by:

    1. Boris HirschBy & Daniel S. J. Lechmann & Claus Schnabel, 2017. "Coming to work while sick: an economic theory of presenteeism with an application to German data," Oxford Economic Papers, Oxford University Press, vol. 69(4), pages 1010-1031.

    More about this item

    Keywords

    Presenteeism; sickness absence; labor supply; cost-of-illness; economic evaluation; count models;

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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