1 Is work absence contagious? Patrik Hesselius, Per Johansson and Johan Vikström Department of Economics, Uppsala University and IFAU

2 Motivation for investigating social interactions Large differences, in for example work absence, between countries, regions and over time The differences could hardly be explained only by institutions!? Social interactions could be one explanation

3 Sickness absence in six countries

4 Sickness absence in Sweden

5 Identification problem Four explanations to segregation in work absence: Endogenous interactions Absence varies with the overall behavior Exogenous interactions Varies with exogenous characteristics in the network Correlated effects A) Institutions differs between networks B) Similar individual characteristics

6 Earlier studies on int. in social insurance Unemployment: Clark (2003), Topel (2001), Topel & Conley (2001) Åberg, Hedström & Kolm (2003) Work absence Ichino & Maggi (2000), Lindbeck, Palme & Persson (2004) Conclusion: Social interactions seem to be important Identification need that certain members for some exogenous reason starts to be more absent /or change network

7 This paper Adds to the literature on empirical evidence of social interactions by utilize a randomized experiment in Gothenburg 1988, that previously have shown to increase sickness absence of those randomized into treatment. It introduces exogenous variation Enables identification of endogenous social interactions We find evidence of endogenous effects

8 Outline Swedish sickness insurance (in 1988) The randomized experiment Identification strategy Data and first evidence Theory Results Summing up

9 Swedish sickness insurance (in 1988) Benefits if absent from work due to sickness Covers all employed workers, and nationally financed by proportional pay roll taxes 90 percent replacement rate (up to a ceiling) No qualification day and no experience rating (all benefits paid from the government) Benefits paid for a week before checking the claimants’ eligibility through doctor’s certificate (though possible for the public insurance offices to monitor more strictly)

10 The randomized experiment In the second half of 1988 in Gothenburg municipality Randomized (born on even date) The treated was allowed to receive benefits for two weeks instead of one week without showing a doctor’s certificate Non-blind experiment (large information campaigns) Effects of less strict control of eligibility; i)Increases the duration of absence (short-term absence, until day 14 of a spell) ii)No significant effect on the incidence into sickness absence

11 Fraction still absent before the experiment

12 Fraction still absent during the experiment

13 Identification Four requirements need to be fulfilled in order to use a intervention for identification of social interactions. (i)Cannot change the group composition (ii)Can only affect a proportion of the individuals in each network and the proportion have to differ between at least some of the groups (iii)Exogenous with respect to unobserved variables (iv)The treated must be representative for the network

14 Our setup Ethnicity (country of origin) as network definer Use immigrants in the whole Gothenburg MA =>Different proportion of treated, depending on were their network members live Data for all individuals also before the experiment =>Control for individual (and network) heterogeneity in sickness absence behavior Randomly selected treated =>Treated and non-treated representative for the whole network

15 Data and sample selection Population database; from IFAU database (individual and employment characteristics) and National Security Board (sickness absence) Use working immigrants in age Immigrants from 84 countries with more than 10 members in Gothenburg MA Large immigrant groups: Nordic countries, Hungary, Former Yugoslavia, Poland, Germany, Iran, Turkey and Chile Large variation in proportion treated (23 – 52 percent) and in mean short-term absence (2.7 – 9.1percent)

16 A first look at the data

17 A first look at the data (cont)

18 Theory Include social utility into a regular labor supply model Follows Brock and Durlauf (2000) Assumes rational expectations and that all individuals in the network is given equal weight Individual absence in presence of endogenous interactions depend on the mean absence in the network

19 Estimation Control for network heterogeneity (network fixed effects) Control for seasonal effects (seasonal dummies) Control for network specific trends (allow for correlation between treated and non treated absence also before the reform Sensitivity analysis (artificial treatments for 1987, 1989 and Stockholm)

20 Results - OLS

21 Results – Hazard regressions

22 Results – Hazard regressions (cont)

23 Results – Incidence into work absence

24 Summing up and conclusions A 10 percent increase in the means absence => decrease hazard from work absence by about 1.5 percent because of endogenous interactions. No social interaction effect on the incidence into work absence Sensitivity analysis shows that the results are robust