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The rise in absenteeism: disentangling the impacts of cohort, age and time


In recent years, a number of welfare state economies, including Norway, have experienced substantial increases in sickness absence. Using longitudinal individual register data for virtually all Norwegian employees, we examine the remarkable rise since the early 1990s, with emphasis on disentangling the roles of cohort, age, and time. We show that individual age-adjusted absence propensities have risen even more than aggregate absence rates from 1993 to 2005, which casts doubt on the popular hypotheses that the rise was due to the inclusion into the workforce of young or marginal workers with weaker work-norms or poorer health.

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  1. Data for all physician-certified absence spells are available only from 2001; hence it is not possible to use these data to examine the developments of absenteeism in the 1990’s. In 2005, the sickness absence paid for by SSA accounted for approximately 75% of all absence days in Norway. A detailed examination of physician-certified absences from 2001 and onwards is provided by Markussen et al. (2011).

  2. We exclude persons employed directly by the state for the reason that their sickness insurance payments were not recorded by the SSA at the beginning of our data period. Note also that until April 1, 1998, the employer covered only the first 14 days of the absence spell (rather than the first 16). Hence, there is a break in our data series in 1998 causing a slight decline in the level of recorded absence.

  3. This rise occurred despite general improvements in self-reported health conditions. According to Statistics Norway’s level-of-living surveys, the proportion of the population reporting poor or very poor health declined from 10% in 1995 to 8% in 2005 among citizens above 45 years, while it remained stable at 3% among younger citizens. Based on a sample survey on self-reported health complaints and actual absence behavior in 1996 and 2003, Ihlebaek et al. (2007) found that while the prevalence of health complaints remained stable, sickness absence rose by 65%.

  4. This model is described and discussed in, e.g., Chamberlain (1984, Section 3.2), Lechner et al. (2008, Section 7.3), Baltagi (2008, Section 11.1), and Hilbe (2009, Section 4.1).

  5. Let (t r ,a r ) be the reference year and reference age, respectively, with c r  = t r  − a r . Take a person in cohort c at time t and age a (so that t − a = c) with time dummies t j (t j  = 1 for j = t) and a j (a j  = 1 for j = a). We then have that \(\sum\nolimits_j {(j-t_r )t_j } -\sum\nolimits_j {(j-a_r )a_j } =t-t_r -(a-a_r )=c-c_r \), which is obviously constant within each individual.

  6. The average within-year difference in the absence rate between men aged 37 and 38 and women aged 42 and 43 (1993–2005) are both around 0.01 percentage points.

  7. Recall that there was a break in the data-series in 1998. Before April 1998, spells exceeding 14 days were recorded. After that date, only spells exceeding 16 days were recorded. This implies that our estimates underrate the rise in 1998 (which probably explains why the rise was particularly low in 1998).

  8. When we drop the data from 2004 and 2005, we lose 11% of the analysis population for men and 10% of the population for women.


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This paper is part of the project “Absenteeism in Norway—Causes, Consequences, and Policy Implications”, financed by the Norwegian Research Council (grant #187924). We thank the Editor and two anonymous referees for useful comments.

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Correspondence to Knut Røed.

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Biørn, E., Gaure, S., Markussen, S. et al. The rise in absenteeism: disentangling the impacts of cohort, age and time. J Popul Econ 26, 1585–1608 (2013).

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  • Sick leave
  • Work-norms
  • Multicollinearity

JEL Classification

  • C23
  • I38
  • J22