PhD Day Faculty of Economics and Business Administration 25/05/2012 STIJN BAERT BAS VAN DER KLAAUW GIJSBERT VAN LOMWEL THE EFFECTIVENESS OF OCCUPATIONAL DOCTORS AND SPECIALISTS IN THE REDUCTION OF SICKNESS ABSENTEEISM AMONG SELF-EMPLOYED

Baert, van der Klaauw, van Lomwel (2012) 2 WHY THE ANSWER MAY BE “YES” Moral hazard in public sickness insurance is found among employees Higher sick leave benefits lead to higher sick leave durations (Johansson & Palme, 2005) Gatekeeping by physicians is found to be important to reduce sick leave among them Postponing certificate requirement led to higher sick durations in SE (Hesselius et al., 2005) Stricter regulations for certification led to lower sick durations in NO (Markussen, 2010) ARE OCCUPATIONAL DOCTORS AND SPECIALISTS EFFECTIVE IN REDUCING SICK LEAVE DURATIONS AMONG SELF-EMPLOYED? RESEARCH QUESTION

Baert, van der Klaauw, van Lomwel (2012) 3 WHY THE ANSWER MAY BE “NO” The evidence for employees may not be generalised to the self-employed Self-employed: financial motives to keep absence durations as short as possible Self-employed: more satisfied and involved with their jobs (Blanchflower and Oswald, 1998) Self-employed: need for achievement, love of independence, optimism (Parker, 2004) Private instead of public health cover ARE OCCUPATIONAL DOCTORS AND SPECIALISTS EFFECTIVE IN REDUCING SICK LEAVE DURATIONS AMONG SELF-EMPLOYED? RESEARCH QUESTION

Overview 1.Institutional settings and data 2.Econometric model 3.Results 4.Conclusion Baert, van der Klaauw, van Lomwel (2012) 4

Private insurance system  In the Netherlands, sickness insurance for the self-employed is only available from private insurance companies  We analyse database of major private Dutch insurance company  Two importance modalities of insurance contract:  Deferment period: time period between falling sick and start of benefit payment  Insured income  Active case management in order to enhance recovery rates  Intake interview and monitoring by case workers  Intervention: medical track and labour track Baert, van der Klaauw, van Lomwel (2012) 5 1 | Institutional settings and data

Intervention: medical track and labour track  Medical track  Occupational doctors (physicians)  Second opinion  Further medical treatment  Labour track  Occupational specialists (work study practitioners)  Ergonomic advise  Coaching Baert, van der Klaauw, van Lomwel (2012) 6 1 | Institutional settings and data

Data selection (1)  All sickness claims (11872) between January 2009 and December  Durations until (i) recovery, (ii) medical track and (iii) labour track  From the start of the deferment period (daily precision)  Censored if sick leave had not been terminated at 31 December  For each claim: wide range of individual characteristics  Exclusion of...  Maternity claims (958) and claims with a missing diagnosis type (215).  Claims with missing explanatory variables (31)  Claims with non-positive or inconsistent durations (18) Baert, van der Klaauw, van Lomwel (2012) 7 1 | Institutional settings and data

Data selection (2)  Distinction between 9588 physical and 1062 psychological claims  Patterns of recovery differ by type of disease Baert, van der Klaauw, van Lomwel (2012) 8 1 | Institutional settings and data Figure: survival function for recovery

Data selection (3)  Distinction between 9588 physical and 1062 psychological claims  Patterns of inflow into the intervention tracks differ by type of disease Baert, van der Klaauw, van Lomwel (2012) 9 1 | Institutional settings and data Figure: survival function for labour track

Double selection problem  Problem 1: correlation between unobserved determinants of recovery and intervention  Recovery and intervention may be determined by the same unobservables  This may lead to a spurious relationship  Problem 2: dynamic selection  To evaluate the effect of intervention, the self-employed should not recover before moment of start of intervention  They must therefore have relatively adverse unobserved characteristics  This may bias the estimated intervention effect towards zero  Solution: Timing of Events approach (Abbring & van den Berg, 2003) Baert, van der Klaauw, van Lomwel (2012) 10 2 | Econometric model

Timing of Events approach  Treatment (1): medical track  Treatment effect (1): effect of medical track on recovery rate afterwards  Treatment (2): labour track  Treatment effect (2): effect of labour track on recovery rate afterwards  Use time variation in treatments in order to capture treatment effects Baert, van der Klaauw, van Lomwel (2012) 11 2 | Econometric model

Econometric framework  r: index recovery; m: index medical track and l: index labour track  : hazard rates  t: elapsed durations since start job search  λ: baseline hazards (piecewise constant)  x : vector of observables; v: unobservables (discrete distribution) Baert, van der Klaauw, van Lomwel (2012) 12 2 | Econometric model Econometric framework

Constant treatment effect model Baert, van der Klaauw, van Lomwel (2012) 13 3 | Results Econometric framework Constant treatment effect model Baert, van der Klaauw, van Lomwel (2012) Estimation results treatment effects Physical claimsPsychological claims Medical track:Constant m, *** (0.05)0.13 (0.36) Labour track:Constant l, *** (0.09)0.06 (0.23)

Extended model Baert, van der Klaauw, van Lomwel (2012) 14 3 | Results Econometric framework Extended model Estimation results treatment effects Physical claimsPsychological claims Medical track: Constant Early intervention Middle late intervention -0.62*** (0.06) (0.08) (0.06) ** 0.59*** (0.36) (0.20) (0.18) Labour track: Constant Early intervention Middle late intervention -0.76*** (0.10) (0.23) (0.13) (0.27) (0.20) (0.15)

Sensitivity analysis 1: delay start of durations Baert, van der Klaauw, van Lomwel (2012) 15 3 | Results Econometric framework Extended model Estimation results treatment effects Physical claimsPsychological claims Medical track: Constant Early intervention Middle late intervention -0.63*** (0.06) (0.08) (0.06) ** 0.57*** (0.36) (0.21) Labour track: Constant Early intervention Middle late intervention -0.76*** (0.10) (0.22) (0.12) (0.28) (0.18) (0.16)

Sensitivity analysis 2: gender heterogeneity Baert, van der Klaauw, van Lomwel (2012) 16 3 | Results Econometric framework Other dimensions effect heterogeneity Baert, van der Klaauw, van Lomwel (2012) Estimation results treatment effects Physical claimsPsychological claims Medical track: Constant Female -0.56*** 0.06 (0.05) (0.09) * (0.36) (0.27) Labour track: Constant Female -0.78*** 0.01 (0.09) (0.14) (0.23) (0.25)

Sensitivity analysis 3: tough occupations Baert, van der Klaauw, van Lomwel (2012) 17 3 | Results Econometric framework Other dimensions effect heterogeneity Baert, van der Klaauw, van Lomwel (2012) Estimation results treatment effects Physical claimsPsychological claims Medical track: Constant Tough occupation -0.60*** 0.05 (0.08) (0.07) (0.35) (0.23) Labour track: Constant Tough occupation -0.46*** -0.48*** (0.11) (0.10) * (0.27) (0.23)

Conclusion  Only stable positive effect of early and middle late intervention by occupational doctors for psychological claims  All other forms of intervention have a neutral or negative effect  Self-employed have every interest in keeping absence durations as short as possible  Occupational doctors and specialists may advise longer sick-leaves than necessary (Hesselius et al., 2005)  Occupational doctors and specialists may be unable to distinguish shirkers from truly sick (Carlsen and Nyborg, 2009) Baert, van der Klaauw, van Lomwel (2012) 18 4 | Conclusion