1. Does Delay Cause Decay? The Effect of Administrative Decision Time on the Labor Force Participation of Disability Applicants David Autor, MIT and NBER Nicole Maestas, RAND Kathleen Mullen, RAND Alexander Strand, SSA Retirement Research Consortium Annual Conference August 2012 MRRC (SSA) funding gratefully acknowledged (UM11-01) C ENTER for D ISABILITY R ESEARCH

2. Disability and labor supply Large body of research studies effects of DI receipt on labor supply, but ignores role of application process DI applicants spend months or years seeking benefits If employment potential deteriorates while out of labor force, then their subsequent LFP understates employability at time of application This has implications for total cost of DI program and previous estimates of receipt effect 2

3. Our contribution This paper tests whether the duration of the DI application processwaiting timecausally affects subsequent employment Since waiting times are likely to be (negatively) correlated with unobserved severity, we use an IV strategy We exploit variation in applicant waiting times resulting from variation in average initial processing times of disability examiners 3

4. DI application process Local Field Office Screens out applicants earning >= $1,010/month State DDS Office Assigns case to disability examiner who makes initial determination Appeals Process Denied applicants may appeal (four levels) 4

5. Data 5 Disability Operational Data Store (DIODS) Administrative database linking applicant-examiner Universe of initial applications decided in 2005, recon decisions in 2005-2006 Link to other administrative databases to obtain ultimate outcomes and decision dates through 2010 (CPMS, PHUS, MBR) Link to Detailed Earnings Record (DER) to construct labor supply measures Uncapped earnings (Medicare box on W-2)

6. Summary statistics 1,128,388 applications 67% receiving DI benefits by 2010 33% initially allowed 67% initially denied 60% appeal to recon or ALJ 70% allowed on appeal 37% musculoskeletal 22% mental Mean age 47 years Mean earnings $22K 6

7. Summary statistics Initially allowed Allowed on appeal or reappl. Initially denied, denied on appeal Initially denied, no appeal No. observations373,851379,187115,698259,652 % of sample33.1%33.6%10.3%23.0% Time at DDS (months)2.8 (1.8) 3.1 (1.6) 2.9 (1.6) 2.8 (1.6) Total processing time3.8 (2.7) 24.3 (16.3) >23.2 (19.2) >3.7 (2.2) Note: total processing times censored for applicants denied at higher level appeals (appeals council or federal court) or those pursuing reapplication 7 Two-thirds of applicants awarded benefits within 5 years of application 50% of awards made on appeal

8. Empirical strategy Two key assumptions: 1. Conditional random assignment of examiners to applicants 2. Monotonicity Holding case characteristics constant, some examiners faster than others Cases processed by fast examiners would take longer if processed by slow examiners, and vice versa 8

9. Estimated Examiner-Specific Processing Times 9

10. First stage results Coefficient on EXTIME in regression of FINAL TIME on EXTIME All Initially allowed Initially denied No control variables1.4710.9061.574 (0.045)(0.010)(0.042) Plus assignment variables (DDS, TERI, body system) 0.9860.8471.062 (0.029)(0.012)(0.027) Plus individual characteristics (age, pre- onset earnings, zip) 0.9660.8401.031 (0.027)(0.012)(0.034) No. observations 1,128,388373,851754,537 Mean dependent variable is 12.6, mean EXTIME is 2.9. Std errors clustered on examiner in parentheses. 10

11. Reduced form results Coefficient on EXTIME in regression of labor force participation (LFP) on EXTIME Dependent variableAll Initially allowed Initially denied LFP 2 years later (2007)-0.005-0.003-0.006 (0.0007)(0.0010)(0.0009) LFP 3 years later (2008)-0.005-0.004-0.006 (0.0007)(0.0010)(0.0009) LFP 4 years later (2009)-0.004-0.003-0.004 (0.0007)(0.0009) No. observations 1,128,388373,851754,537 Full controls. Mean dependent variable is 0.13 in 2007, 0.13 in 2008, 0.12 in 2009, mean EXTIME is 2.9. Std errors clustered on examiner in parentheses. 11

12. Can we interpret causally? Our reduced form estimate is a causal effect of examiner speed on LFP To interpret as casual effect of waiting time on LFP: Requires: EXTIME only affects LFP through waiting time In the paper we show that EXTIME is Uncorrelated with initial decision, but Slightly correlated with probability of appeal, and eventual DI receipt We can interpret as causal effect of waiting time only for initially allowed For other groups, multiple channels operative: Most important: EXTIME Pr[appeal] Pr[award] 12

13. Effect of waiting time on employment Initially allowed applicants No. obs.Mean LFPOLSIV 2 years-2007373,8510.045-0.0006-0.0037 (0.0002)(0.0012) 3 years-2008361,6250.046-0.0010-0.0047 (0.0002)(0.0012) 4 years-2009346,8480.041-0.0009-0.0032 (0.0002)(0.0011) Control variables include DDS dummies, TERI flag, body system codes, age group dummies, avg. previous earnings and 3-digit zip codes. Std errors clustered on examiner in parentheses. 13

14. Limitations and next steps Not clear if results generalizable beyond initially allowed DI beneficiaries obviously face different work incentives than denied applicants Need an instrument for DI receipt… We have one! Build on Maestas, Mullen and Strand (2011): Use examiner allowance propensities to instrument for receipt 14

15. Summary of findings We find that examiner processing times are negatively correlated with applicants subsequent employment Causally, we can attribute lower employment to longer processing times for initially allowed applicants A one standard deviation (2.4 month) increase in initial processing times reduces subsequent employment rates by ~1 pp Extrapolating to average total processing times, this implies the DI application process reduces employment prospects by ~5 pp (17%) 15

16. C ENTER for D ISABILITY R ESEARCH

17. Overview of databases Disability Operational Data Store (DIODS) Initial applications (2005) and reconsideration decisions (2005-2006) Case Processing and Management System (CPMS) Administrative Law Judge (ALJ) decisions (2005-July 2011) Payment History Update System (PHUS) and Master Beneficiary Record (MBR) Higher appeals and reapplications (2005-2010) 17