Occupational Hazards and Social Disability Wash U

Transcription

1 Occupational Hazards and Social Disability Wash U Amanda M. Michaud David Wiczer Indiana University FRB St. Louis February 17, 2014 A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

2 Intro Introduction A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

3 Intro What we re after How does one s occupational choice contribute to later work disabilities? How does this affect the desirability of DI? 1 Provides individual-level insurance (risk sharing) 2 Affects occupational choice (reallocation) A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

4 Intro What we are doing and why it is a good approach We think of occupations as: Imperfectly substitutable labor Disability risk to workers A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

5 Intro What we are doing and why it is a good approach We think of occupations as: Imperfectly substitutable labor Disability risk to workers Incomplete markets for risk implies: 1 A wage premium to the partially uninsurable disability risk 2 Relative to the social planner, there is too little labor in the risky occupations A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

6 Intro What we are doing and why it is a good approach We think of occupations as: Imperfectly substitutable labor Disability risk to workers Incomplete markets for risk implies: 1 A wage premium to the partially uninsurable disability risk 2 Relative to the social planner, there is too little labor in the risky occupations (1) is large DI has smaller gains; (2) is large DI bigger gains A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

7 Intro The pin factory Pin makers recruit for two types of jobs: 1 Lift heavy vats of molten metal 2 Spit shine the pins A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

8 Intro The pin factory Pin makers recruit for two types of jobs: 1 Lift heavy vats of molten metal 2 Spit shine the pins DI improves lifters welfare: they are imperfectly insured. DI improves spitters welfare: there are more lifters and the factory is more efficient. A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

9 Intro Summary of results Risky occupations have 56% higher rates of disability 26% will report difficulty with an ADL versus 17% 62% of that is the occupation effect, i.e. not explained by observables. A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

10 Intro Summary of results Risky occupations have 56% higher rates of disability 26% will report difficulty with an ADL versus 17% 62% of that is the occupation effect, i.e. not explained by observables. DI is Pareto improving: An ɛ increase in benefit/tax improves everyone s welfare There is a unique optimal level, which depends on the degree of substitutability and risk aversion. Welfare gains are U -shaped in elasticity of substitution A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

11 Statistics on Disability by Occupation Statistics on Disability by Occupation A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

12 Statistics on Disability by Occupation Connecting past occupational exposure to future disability The distribution of disability by occupation has a very long tail: Any Difficulties in Activities of Daily Life Fraction of occupations ADL Density Estimate Mean Figure : The distribution of limitations to activities of daily life A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

13 Statistics on Disability by Occupation Associating workers with occupations We want to associate a worker s late-life health outcome with his work history HRS has 17 occupation categories, 2-digit SOC. Use the longest-held occupation (70% match with current occupation). HRS is a panel and longest-held is asked each wave Use the longest longest-held (only inconsistent <1%) E[Tenure] = 19.8, sd[tenure] = 11.2 A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

14 Statistics on Disability by Occupation Constructing Disability Our primary measure is an indicator for any difficulty with ADLs: Follow Wallace & Herzog (J Human Res, 1995) Activities: Walk a block; Climb flight of stairs; Lift 10 lbs; Stoop/kneel/crouch; Arms over shoulders 50% receive DI and 65% apply if have a difficulty Workers also self-report a health-related limitation to work: Any health impairment that limits the kind or amount of work 38% receive and 57% apply for DI if have a limitation With both, we only count disability before 65 A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

15 Statistics on Disability by Occupation Percent with any disability Each observation is an occupation s mean, population weighted: Any Difficulties in Activities of Daily Life Fraction of occupations ADL Density Estimate Mean Figure : The percent with any of limitation to activities of daily life A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

16 Statistics on Disability by Occupation Distribution of number of disabilities The distribution looks the same when we consider the number of disabilities: Number of difficulties in ADLs Fraction of occupations ADLs Density Estimate Mean Figure : Metric over the number and severity of limitations to activities of daily life A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

17 Statistics on Disability by Occupation Distribution of health limitations: Health Limitations Fraction of occupations Health Limitations Density Estimate Mean A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

18 Statistics on Disability by Occupation Splitting the occupations By health limitations or ADL difficulty, the top third are: Occupation Fraction Health Services 5.94 Mechanics/Repair Construction/Extraction Precision Production Machine Operators Transportation Operators Handlers 8.40 Military 3.44 A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

19 Statistics on Disability by Occupation These workers look very different Safer Riskier BMI (0.04) (0.04) Woman 0.57 (0.00) 0.43 (0.00) Entrep 0.29 (0.00) 0.22 (0.00) College 0.62 (0.00) 0.37 (0.00) <HS 0.11 (0.00) 0.29 (0.00) Non-married 0.17 (0.00) 0.19 (0.00) Non-white 0.11 (0.00) 0.16 (0.00) Smoker 0.17 (0.00) 0.23 (0.00) A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

20 Statistics on Disability by Occupation Decomposing disability risk We do a Oaxaca decomposition between the two groups (1) (2) (3) (4) Safer Riskier Difference Observables % of difference Coefficients Interaction % of difference N 20, ,138 20, ,138 Table : (1)&(2) are ADL difficulties, (3)&(4) are health limitations. (1)&(3) count one observation per individual, (2)&(4) count each wave A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

21 Simple Model A Simple Model of Occupation Choice and Disability A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

22 Simple Model A simple model technology OLG with 2 periods A discrete number of occupations indexed, j = 1,..., J For each j, θ j, is the disability probability 1 θ j work in the second period Aggregation by CES y = ( j nγ j ) 1/γ where nj = l j (2 θ j ). A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

23 Simple Model A simple model workers problem Workers have incomplete markets: only a single asset They choose to work in one occupation for their whole lives No discounting and strictly risk averse instantaneous utility The problem is: max u ( w j a ) + θ j u (a) + (1 θ j )u ( w j + a ) (1) {j,a} A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

24 Simple Model Social Planner s allocation We can fully characterize the efficient allocation solving the SP problem For any two occupations, θ, θ the allocation satisfies (2 θ j ) γ l γ 1 j = (2 θ k ) γ l γ 1 k Integrate this up to satisfy the population constraint, j l j = 1 A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

25 Simple Model The complete markets allocation is efficient We can set up the problem with full arrow securities: i.e. bonds conditional on θ j choice and disability status Consumption, c is equalized across states and occupations Wages: This means w j = 2c 2 θ j ( 2c l j = 2 θ j ) γ γ 1 A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

26 Simple Model The incomplete markets allocation under-supplies risky workers Theorem The distribution {l j } J j=1 complete markets. is FOSD by {lcm j } J j=1, the allocation with T l cm < j=1 T l j T {1,.., J} j=1 Workers choosing occupations men they are indifferent between all of them Risk aversion implies j, k : θ j > θ k then w j w k w cm j wk cm This implies labor for θ j are relatively lower in IM than CM, l j l k lcm j l cm k A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

27 Simple Model What the equilibrium looks like: σ CM is unaffected, but as risk aversion, IM is more efficient Figure : Labor distribution with various σ, u(c) = c1 σ 1 σ A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

28 Simple Model What the equilibrium looks like: γ The IM allocation is more inefficient as elasticity. Figure : Labor distribution with various γ A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

29 Simple Model The marginal utility of disability insurance Theorem Let EU(b) be the expected utility from a competitive allocation with lump-sum benefit b. Then EU (0) > 0 and b : EU (b) = 0 Workers facing disability risk (θ j > 0) benefit because of the insurance and if θ = 0, their wages are higher For b high enough, EU (b ) < 0. EU ( ) is continuous, hence, b : EU (b ) = 0 A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

30 Simple Model Disability insurance average effects DI increases disability but also improves welfare, to a point. A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

31 Simple Model Disability insurance welfare distribution Consider the old generation when DI is introduced: their choice is not distorted. Even the non-disabled benefit through higher wages because of the youngs better choices A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

32 Quantitative Evaluation Quantitative Evaluation A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

33 A calibrated exercise Quantitative Evaluation We will use the HRS data to calibrate the model: J=2, with {θ l, θ h }, high and low risk. Production is CES with n l in low risk and n h in high risk Y = A ( αn γ l + (1 α)nγ h Match in the data: The fraction in risky/non-risky occupations The difference in risk levels ) 1 γ A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

34 Quantitative Evaluation The welfare gain is non-monotone Welfare Gains by Elasticity of Substitution Occupation specific risk IID risk Welfare Gain (relative to no insurance) Elasticity At low and high elasticity, the welfare gain is greater. Compare this to the benchmark where all disability risk is IID. A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

35 Quantitative Evaluation Intuition for non-monotonicity Two effects 1 At low elasticity, DI makes the economy more productive More sort into high risk occupations Complementary to low-risk producers 2 At high elasticity, the wages do not compensate much for risk With a lower wage premium, agents cannot self-insure as well DI helps by providing a contingent claim. A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

36 Quantitative Evaluation The optimal DI benefit reduces output 1.15 Change in Output by Elasticity of Substitution 1.1 Output (relative to no insurance) Elasticity For high enough elasticity, the welfare maximizing DI reduces output. A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

37 Quantitative Evaluation Labor allocation is not output-maximizing 1 Change in Labor Allocation by Elasticity of Substitution Labor in Safe Occupation Elasticity Unless production is Leonteif, optimal welfare skews labor away from the safe occupation A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

38 Conclusion Conclusion A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

39 Conclusion Recap We showed: Disability outcomes differ substantially across occupations Insurance is Pareto improving The welfare gains may be very small 1 The gains from reallocation are large when occupations are complements 2 The gains from consumption insurance are large when occupations are substitutes Follow up: How should we estimate the elasticity of substitution? A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36

40 A brief advertisement Conclusion This is part of a larger research agenda that could be summarized as: Disability shocks are not IID What is the optimal design of a DI program given that some risk can be forecasted (and how much is that?) How much do people know of their own disability risk? Can we infer it from savings? A Michaud, D Wiczer (IU, FRB StL) Occupational Hazards February 17, / 36