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“…For instance, since high absence rates may reduce the chances of obtaining a permanent contract, employees with temporary jobs like fixed-term contracts can be expected to signal effort and thus show lower absenteeism. This has been found 6 When information on workers' satisfaction with income or wages is missing, some studies include workers' (relative or absolute) wages (see, e.g., Pfeifer 2010, Arnold et al 2018). We will not make use of the wage variable since our data set provides the better-suited income satisfaction variable and since the wage variable has many missing values, so that including it would reduce our estimation sample by 17 percent.…”
Section: Theoretical Considerations and Empirical Literaturementioning
confidence: 99%
“…It is common for empirical studies of absence from work to include socio-demographic characteristics of employees such as age, sex, qualification, household context and nationality as potential explanatory variables even if the theoretical basis of their inclusion is often weak (see the literature reviews by Allebeck andMastekaasa 2004 andBeemsterboer et al 2009, as well as Beblo and Ortlieb 2012, Störmer and Fahr 2013, and Arnold et al 2018 for Germany). Empirical findings vary considerably and partly seem to depend on whether the crucial determinants discussed above such as health status, working conditions, and job (dis)satisfaction have also been included in the analysis.…”
Section: Theoretical Considerations and Empirical Literaturementioning
confidence: 99%
“…Starting with health status, it is possible that those people working in the public sector are simply not as healthy as their counterparts in the private sector and thus are absent from work more often. To tackle this question, we can make use 10 The overall figures for the incidence and length of sickness absence in our data set are in the same ballpark as those reported in the GSOEP (see Arnold et al 2018, Table A1, although they do not distinguish between the public and private sector). We are aware that our sick-leave data (like those of the GSOEP) might suffer from recall and reporting bias.…”
Section: Data and Descriptive Evidencementioning
confidence: 99%
“…4 The empirical evidence is also mixed for Germany: In some studies, the public sector dummy points to higher sickness absence in this sector (see, e.g., Pfeifer 2013). A recent analysis with GSOEP data by Arnold et al (2018) reports sickness incidence to be 11.6 percent higher and sickness days to be about 1.5 days higher in the public sector, ceteris paribus. In contrast, other studies find increased absenteeism in the public sector only for certain groups of workers such as men or white-collar employees (Thalmaier 2002, Störmer andFahr 2013).…”
SUMMARY
Public sector employees are often said to have excessive rates of absence from work. Using representative survey data for Germany, we indeed find absenteeism of employees to be higher in the public than the private sector. The differences in the incidence and days of absence showing up in descriptive statistics are substantially reduced and partly disappear in our estimates of hurdle regression models controlling for individuals’ socio‐demographic characteristics, health status, professional activities, and for many workplace‐related factors. Nevertheless, the probability of staying home sick at least once a year is still 5.6 percentage points higher in the public sector, ceteris paribus. This finding refutes popular assertions that differences in absence rates between the sectors are mainly due to structural factors like different compositions of the workforce. We show that the same observable factors play a role for absenteeism in the public and private sector, but we cannot rule out that shirking may play a more important role in the public sector. Nevertheless, we conclude that the stereotype of the “malingering bureaucrat” seems to be an exaggeration, at least for Germany.
“…For instance, since high absence rates may reduce the chances of obtaining a permanent contract, employees with temporary jobs like fixed-term contracts can be expected to signal effort and thus show lower absenteeism. This has been found 6 When information on workers' satisfaction with income or wages is missing, some studies include workers' (relative or absolute) wages (see, e.g., Pfeifer 2010, Arnold et al 2018). We will not make use of the wage variable since our data set provides the better-suited income satisfaction variable and since the wage variable has many missing values, so that including it would reduce our estimation sample by 17 percent.…”
Section: Theoretical Considerations and Empirical Literaturementioning
confidence: 99%
“…It is common for empirical studies of absence from work to include socio-demographic characteristics of employees such as age, sex, qualification, household context and nationality as potential explanatory variables even if the theoretical basis of their inclusion is often weak (see the literature reviews by Allebeck andMastekaasa 2004 andBeemsterboer et al 2009, as well as Beblo and Ortlieb 2012, Störmer and Fahr 2013, and Arnold et al 2018 for Germany). Empirical findings vary considerably and partly seem to depend on whether the crucial determinants discussed above such as health status, working conditions, and job (dis)satisfaction have also been included in the analysis.…”
Section: Theoretical Considerations and Empirical Literaturementioning
confidence: 99%
“…Starting with health status, it is possible that those people working in the public sector are simply not as healthy as their counterparts in the private sector and thus are absent from work more often. To tackle this question, we can make use 10 The overall figures for the incidence and length of sickness absence in our data set are in the same ballpark as those reported in the GSOEP (see Arnold et al 2018, Table A1, although they do not distinguish between the public and private sector). We are aware that our sick-leave data (like those of the GSOEP) might suffer from recall and reporting bias.…”
Section: Data and Descriptive Evidencementioning
confidence: 99%
“…4 The empirical evidence is also mixed for Germany: In some studies, the public sector dummy points to higher sickness absence in this sector (see, e.g., Pfeifer 2013). A recent analysis with GSOEP data by Arnold et al (2018) reports sickness incidence to be 11.6 percent higher and sickness days to be about 1.5 days higher in the public sector, ceteris paribus. In contrast, other studies find increased absenteeism in the public sector only for certain groups of workers such as men or white-collar employees (Thalmaier 2002, Störmer andFahr 2013).…”
SUMMARY
Public sector employees are often said to have excessive rates of absence from work. Using representative survey data for Germany, we indeed find absenteeism of employees to be higher in the public than the private sector. The differences in the incidence and days of absence showing up in descriptive statistics are substantially reduced and partly disappear in our estimates of hurdle regression models controlling for individuals’ socio‐demographic characteristics, health status, professional activities, and for many workplace‐related factors. Nevertheless, the probability of staying home sick at least once a year is still 5.6 percentage points higher in the public sector, ceteris paribus. This finding refutes popular assertions that differences in absence rates between the sectors are mainly due to structural factors like different compositions of the workforce. We show that the same observable factors play a role for absenteeism in the public and private sector, but we cannot rule out that shirking may play a more important role in the public sector. Nevertheless, we conclude that the stereotype of the “malingering bureaucrat” seems to be an exaggeration, at least for Germany.
“…On the one hand, matched employer-employee data, which allow constructing detailed workforce characteristics, including absences, have been available for a relatively short time (Card, Devicienti, and Maida 2014). Instead, a vast literature assessing the determinants and dynamics of sickness absenteeism-which resorts to individual-level data-testifies the attention that the academic community has placed on this theme (e.g., Arnold, Br€ andle, and Goerke 2018;Battisti and Vallanti 2013;Dionne and Dostie 2007). Instead, a vast literature assessing the determinants and dynamics of sickness absenteeism-which resorts to individual-level data-testifies the attention that the academic community has placed on this theme (e.g., Arnold, Br€ andle, and Goerke 2018;Battisti and Vallanti 2013;Dionne and Dostie 2007).…”
Using rich longitudinal matched employer-employee data for Belgium, we provide a first investigation of the impact of sickness absenteeism on firms' productivity. To do so, we estimate a production function augmented with a firm-level measure of sickness absenteeism that we constructed from worker-level information on nonworked hours due to illness or injury. We deal with the endogeneity of inputs and sickness absenteeism by applying a modified version of the semiparametric control function method developed by Ackerberg, Caves, and Fraser (2015), which explicitly takes firm fixed unobserved heterogeneity into account. Our main finding is that, in general, sickness absenteeism substantially dampens firms' productivity. However, further analyses show that the impact varies according to several workforce and firm characteristics. Sickness absenteeism is more detrimental to firm productivity when absent workers are high tenure or blue collar. Moreover, it is especially harmful to industrial, capital-intensive, and small enterprises. These findings are consistent with the idea that sickness absenteeism is more problematic when absent workers have in-depth firm-/task-specific knowledge, when the employees' work is highly interconnected (e.g., along the assembly line), and when firms face more organizational limitations in substituting absent workers.
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