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1 Is work absence contagious? Patrik Hesselius, Per Johansson and Johan Vikström Department of...
Transcript of 1 Is work absence contagious? Patrik Hesselius, Per Johansson and Johan Vikström Department of...
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Is work absence contagious?
Patrik Hesselius, Per Johansson and Johan VikströmDepartment of Economics, Uppsala University and IFAU
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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
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Sickness absence in six countries
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1983
1985
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%
FR
DE
NL
NO
SE
UK
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Sickness absence in Sweden 1970-2005
0%
1%
2%
3%
4%
5%
6%
7%
8%
1970 1975 1980 1985 1990 1995 2000 2005
Men
Women
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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
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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
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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
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Outline
• Swedish sickness insurance (in 1988)• The randomized experiment• Identification strategy• Data and first evidence• Theory• Results• Summing up
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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)
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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
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Fraction still absent before the experiment
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Day of sickness absence
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Treatment
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Fraction still absent during the experiment
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Day of sickness absence
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Treatment
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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
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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
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Data and sample selection
• Population database; from IFAU database (individual and employment characteristics) and National Security Board (sickness absence)
• Use working immigrants in age 20-60
• 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)
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A first look at the data
Estimate Standard error t-ratio Non-treated1 Intercept -.540 .048 -11.30 1988 1.011 .067 15.07 1989 .412 .066 6.34 Treated2 Intercept -.431 .080 -5.41 1988 2.445 .110 21.85 1989 0.300 0.11 2.72
Notes: 1n = 73 343, 2n = 32 144
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A first look at the data (cont)
Non-treated Treated Estimate Standard error Estimate Standard error Intercept 0.333 ***0.093 0.91 ***0.20 2nd quartile 0.183 0.121 1.63 ***0.25 3rd quartile 0.072 0.189 0.81 ***0.30 4th quartile 0.232 *0.138 1.22 ***0.27 R2 0.016 % 0.48%
Notes: *** significant at the 1% level, * significant at the 10 % level
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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
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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)
1 1 2 1 , 1,...12.ijm j ijm im ijm ijmy D month m
1( / ) ( , 1)jm j j jn n m R
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Results - OLS
Network Size jn > 10 jn >30 10< jn <1000
Time period and Area
Parameter Estimate Std Error Estimate Std Error Estimate Std Error
1988 1 0.161 **0.079 0.114 0.085 0.110 0.091
2 -0.053 0.085 0.003 0.099 -0.030 0.090
1987 1 0.013 0.092 0.008 0.109 0.034 0.110
2 -0.048 0.085 -0.008 0.108 -0.070 0.090
1989 1 -0.025 0.078 -0.024 0.082 -0.068 0.095
2 0.044 0.079 0.128 0.088 -0.050 0.086
Stockholm MSA 1 -0.021 0.072 -0.031 0.075 0.015 0.127
2 0.551 ***0.090 0.716 ***0.105 0.292 ***0.117
Notes: Robust standard errors. ** and *** denotes significantly different from zero at the 5 and 1 percent level.
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Results – Hazard regressions
Network Size jn > 10 jn >30 10< jn <1000
Time period and Area
Parameter Estimate Std Error Estimate Std Error Estimate Std Error
1988 1 -0.186 **0.072 -0.192 **0.084 -0.174 **0.084
2 0.102 0.078 0.054 0.096 0.108 0.084
1987 1 -0.042 0.108 -0.022 0.120 -0.035 0.126
2 -0.114 0.084 -0.204 0.102 -0.015 0.090
1989 1 0.060 0.072 0.051 0.078 0.021 0.090
2 0.036 0.078 -0.001 0.084 -0.006 0.084
Stockholm MSA 1 -0.042 *0.024 -0.042 * 0.024 -0.066 * 0.042
2 0.042 0.030 0.030 0.036 0.030 0.036 Notes: *, ** and *** denotes significantly different from zero at the 10, 5 and 1 percent level.
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Results – Hazard regressions (cont)
Sensitivity analysis not controlling for general trends
Network Size jn > 10 jn >30 10< jn <1000
Time period and Area
Parameter Estimate Std Error Estimate Std Error Estimate Std Error
1988 1 -0.120 **0.053 -0.156 ***0.058 -0.102 *0,060
Note: *** significant at the 1% level and * significant at the 10% level.
Sensitivity analysis control for; gender, age, age square, government employed, income and parish
Network Size jn > 10
Time period and Area
Parameter Estimate Std Error
1988 1 -0.258 ***0.072
2 0.156 **0.078
Note: *** significant at the 1% level and * significant at the 10% level.
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Results – Incidence into work absence
Network Size jn > 10 jn >30 10< jn <1000
Time period and Area
Parameter Estimate Std Error Estimate Std Error Estimate Std Error
1988 1 0.022 0.016 0.023 0.018 0.017 0.018
2 0.012 0.017 0.014 0.020 0.010 0.019
Notes: *, ** and *** denotes significantly different from zero at the 10, 5 and 1 percent level.
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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