Work Disability, Work, and Justification Bias in Europe and the US

1. Work Disability, Work, and Justification Bias in Europe and the US Arie Kapteyn (RAND) James P. Smith (RAND) Arthur van Soest (Netspar, Tilburg University)

2. Overview • Motivation • Anchoring vignettes, justification bias • Data (HRS & SHARE) • Model for work disability, justification bias, and employment • Estimation and simulation results • Conclusions

3. Motivation • Labor force participation of older workers is policy relevant • Health is a main reason for not participating • Self-reported work disability is a summary measure of work-related health… • But has problems: • Comparability across countries • Justification bias • Anchoring vignettes can be used to tackle these problems

4. This paper… • Demonstrates that anchoring vignettes can be used to analyze justification bias • Uses data on work disability self-reports, work disability vignette evaluations, and employment status from SHARE 2004 and HRS 2004 • Introduces an econometric model which extends the hopit model with an employment equation and accounts for • an effect of employment status on response scales and reported work disability • an effect of work disability on employment • Presents estimates of this model for the US and 8 EU countries

5. Self report of work disability • “Do you have any impairment or health problem that limits the kind or amount of work you can do?” • Response categories: • 1. None • 2. Mild • 3. Moderate • 4. Severe • 5. Extreme/Cannot Do

6. Vignettes • Example (affect): • Henriette generally enjoys her work. She gets depressed every 3 weeks for a day or two and loses interest in what she usually enjoys but is able to carry on with her day-to-day activities on the job. • Does Henriette have any impairment or health problem that limits the kind or amount of work she can do?” • None, Mild, Moderate, Severe, or Extreme/Cannot Do?

7. More examples • Pain Vignette: • Catherine suffers from back pain that causes stiffness in her back especially at work but is relieved with low doses of medication. She does not have any pains other than this generalized discomfort. • Cardio Vascular Disease Vignette: • Norbert has had heart problems in the past and he has been told to watch his cholesterol level. Sometimes if he feels stressed at work he feels pain in his chest and occasionally in his arms. • We work with nine vignettes: three on pain, three on affect, three on CVD

8. How Do Vignettes Work? None John 1 Mary 1 Resp. 1 Liam 1 Extreme

9. How Do Vignettes Work: Differential Item Functioning (DIF) None None John 1 Mary 1 Resp. 1 John 2 Resp. 2 Mary 2 Liam 1 Liam 2 Extreme Extreme

10. How Do Vignettes Work: Adjusting for DIF None None None John 1 John 2 Resp. 2 Mary 1 Mary 2 Resp. 1 John 2 Resp. 2 Mary 2 Liam 1 Liam 2 Liam 2 Extreme Extreme Extreme

11. The data • For a subset of counties that agreed to participate, SHARE wave 1 in 2004 included a set of vignette questions on general health status and on work limiting disabilities as part of a drop-off questionnaire for a random subsample of the 50+ population. • The eight SHARE countries that agreed to participate in the drop-off containing vignette questions were Germany, France, Spain, Belgium, Greece, Italy, the Netherlands, and Sweden. • HRS 2004 administered the same vignettes, in an experimental module administered to a random subsample of the 50+ population in the US

12. Example: pain vignette 1 [Catherine]

13. Red is tough; Blue is soft Rank correlations: (1,2) = 0.44; (1,3) = 0.06; (2,3) = -0.33

14. Correlations between rankings

15. A ranking of toughness

16. Toughness and employment protection

17. Self-reported Work Disability • country | none mild moderate severe extreme • ---------+------------------------------------------ • US | 49.84 21.51 16.02 7.35 5.28 • SHARE-EU | 46.56 25.46 17.37 7.80 2.81 • germany | 40.19 30.04 21.34 7.02 1.41 • sweden | 53.62 15.11 14.86 12.17 4.24 • netherl | 52.05 30.66 9.27 4.92 3.10 • spain | 47.59 20.24 17.21 11.70 3.26 • italy | 46.01 27.04 15.47 7.20 4.27 • france | 49.13 23.02 18.60 6.60 2.65 • greece | 68.32 12.17 10.20 7.43 1.89 • belgium | 36.64 35.22 19.13 6.91 2.11 • ---------+----------------------------------------- • Total | 47.00 24.92 17.18 7.74 3.15

18. Simulation results: Work disability in EU and US(Hopit model)

19. Simulation results: Italy and US(Hopit model)

20. Simulation results: Germany and US(Hopit model)

21. Simulation results: Spain and US(Hopit model)

22. Employment Rates • US 50.16 • SHARE-EU 26.27 • germany 28.42 • sweden 40.82 • netherlands 32.32 • spain 26.34 • italy 20.41 • france 26.42 • greece 25.98 • belgium 21.19 • Total 29.54

23. Work Disability and Employment • US SHARE-EU • ----------------------------- • none 67.61 36.94 • mild 48.70 22.92 • moderate 30.38 13.78 • severe 14.58 8.84 • extreme 0.99 4.54 • ----------------------------- • Total 50.16 26.27

24. Work Disability and Employment

25. Dependent Variables

26. Work Disability Equation

27. Equation for Thresholds

28. Vignette Evaluations

29. Employment Equation

30. Important Assumptions • Response consistency: same thresholds in self-assessments and vignette evaluations • Justification bias = Shift in response scales = a special form of DIF • Vignette equivalence: workers and non-workers and respondents in different countries interpret vignettes in the same way • No causal effect of employment status on health (cf., e.g., Böckerman & Ilmakunnas, Health Economics, 2009)

31. Work Disability EquationModel with DIF • US EU-US Country dummies • Female -0.017 -0.075 constant -0.189 • Married/LT -0.118* 0.078 Germany -0.689* • Educyrs -0.039* 0.034* Sweden -1.066* • Heart prob 0.463* -0.033 Netherlands -0.699* • Lung dis 0.421* -0.098 Spain -0.999* • High blood 0.112* -0.028 Italy -0.895* • Diabetes 0.256* -0.076 France -1.023* • Pain 0.411* 0.048 Greece -1.690* • Arthritis 0.364* -0.038 Belgium -0.654* • Cancer 0.206* 0.209* • Cesd score 0.148* 0.126* *=significant • Obese 0.137* -0.020 at 2-sided • Age 58-64 0.166* 0.004 5% level • Age 65-71 0.135* 0.161* • Age 72+ 0.426* 0.087

32. Work Disability EquationModel without DIF • US EU-US Country dummies • Female -0.106* -0.007 constant -0.126 • Married/LT -0.175* 0.110+ Germany -0.503* • Educyrs -0.046* 0.042* Sweden -0.612* • Heart prob 0.484* -0.027 Netherlands -0.615* • Lung dis 0.423* -0.141 Spain -0.646* • High blood 0.139* -0.065 Italy -0.798* • Diabetes 0.321* -0.110 France -0.848* • Pain 0.426* 0.006 Greece -1.260* • Arthritis 0.354* -0.019 Belgium -0.542* • Cancer 0.142* 0.262* • Cesd score 0.170* 0.114* *=significant • Obese 0.167* 0.004 at 2-sided • Age 58-64 0.157* -0.018 5% level • Age 65-71 0.138* 0.122 • Age 72+ 0.463* 0.010

33. Thresholds Equation(Model with DIF) • US EU-US • Work dummy 0.097* -0.104* • Female 0.096* -0.082* Germany -0.187* • Married/LT 0.051* -0.031 Sweden -0.452* • Educyrs 0.003 -0.004+ Netherlands -0.074+ • Heart prob -0.016 -0.014 Spain -0.356* • Lung dis -0.002 0.037 Italy -0.083* • High blood -0.024+ 0.028 France -0.147* • Diabetes -0.065* 0.069* Greece -0.417* • Pain -0.038* 0.046* Belgium -0.114* • Arthritis -0.005 -0.008 • Cancer 0.066* -0.048 const thrh 1 0 • Cesd score -0.022* 0.008 thr2 - thr1 0.722* • Obese -0.039* 0.014 thr3 - thr2 0.704* • Age 58-64 0.021 0.034 thr4 - thr3 0.822* • Age 65-71 0.020 0.039 • Age 72+ 0.021 0.026 sigma u 0.426* • *, +: significant at 5% and 10% level, respectively

34. Employment Equation (Model with DIF) • US EU-US • work disab -0.464* 0.272* • Female -0.246* -0.319* • Married/LT -0.034 -0.125 constant 0.440* • Educyrs 0.034* -0.020* Germany 0.291 • Heart prob -0.015 -0.002 Sweden 0.784* • Lung dis -0.125 0.002 Netherlands 0.241 • High blood -0.001 0.051 Spain 0.208 • Diabetes -0.228* 0.152 Italy -0.126 • Pain 0.102+ -0.025 France 0.300+ • Arthritis 0.031 -0.058 Greece 0.157 • Cancer 0.004 0.034 Belgium 0.041 • Cesd score -0.051* -0.026 • Obese 0.204* -0.284* *,+: signif. at • Age 58-64 -0.620* -0.406* 5%,10% level • Age 65-71 -1.268* -1.296* • Age 72+ -1.813* -1.402*

35. Employment Equation (Model without DIF) • US EU-US • Work disab. -0.516* 0.319* • Female -0.289* -0.282* • Married/LT -0.069 -0.096 const work 0.473* • Educyrs 0.030* -0.015 Germany 0.310 • Heart prob 0.015 -0.021 Sweden 0.852* • Lung dis -0.102 -0.032 Netherland 0.239 • High blood 0.016 0.034 Spain 0.252 • Diabetes -0.189* 0.122 Italy -0.129 • Pain 0.131* -0.058 France 0.310+ • Arthritis 0.041 -0.066 Greece 0.215 • Cancer -0.023 0.058 Belgium 0.044 • Cesd score -0.035* -0.039 • Obese 0.223* -0.296* *,+: significant • Age 58-64 -0.633* -0.399* at 5%,10% level • Age 65-71 -1.285* -1.288* • Age 72+ -1.815* -1.407*

36. Simulated self-reported work limitations; model including employment equation

37. Employment rates

38. Percent working by disability category

39. Percent working by disability category

40. Conclusions 1 • Norms about what constitutes a work disability vary considerably across countries • Elicitation of norms by vignettes is fairly noisy, but suggests some consistency across domains and the norms appear consistent with legal employment protection • Differences in self-reports are at least partly a reflection of social norms, rather than of “true” disability differences • Scale corrections make a difference for comparing work disability across countries

41. Conclusions 2 • Justification bias is significant in the US but not in SHARE-EU, reflecting different attitudes towards working • Correcting for justification bias reduces the estimated effect of work disability on employment in the US, but not very much • The relation between work disability and work is much stronger in the US than in the EU • Other reasons than health reduce participation among older people in the EU more than in the US