Disability Insurance Benefits and Labor Supply Decisions: Evidence from a Discontinuity in Benefit Awards

Müller, Tobias and Boes, Stefan (2016): Disability Insurance Benefits and Labor Supply Decisions: Evidence from a Discontinuity in Benefit Awards.

Abstract

This paper explores the effects of disability insurance (DI) benefits on the labor market decision of existing DI beneficiaries using data from the Swiss Household Panel. We use a fuzzy regression discontinuity (RD) design to identify the effect of DI benefits on the decision of working full-time, part-time or staying out of the labor force by exploiting a discontinuity in the DI benefit award rate. Overall, our results suggest that the Swiss DI system creates substantial lock-in effects which heavily influence the working decision of existing beneficiaries: the benefit receipt increases the probability of working part-time by about 41%-points, decreases the probability of working full-time by about 42%-points but has little or no effects on the probability of staying out of the labor force for the average beneficiary. Therefore, DI benefits induce a shift in the labor supply of existing beneficiaries in the sense that they reduce their work intensity from working full-time to part-time adding a possible explanation for the low DI outflow across the OECD.

• Item Type: MPRA Paper
• Language: English
• Keywords: Disability insurance benefits, Fuzzy regression discontinuity design, Labor market participation, Endogenous switching models, Maximum simulated likelihood
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C35 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions; J - Labor and Demographic Economics > J2 - Demand and Supply of Labor > J20 - General

References

Angrist, J. D. & Pischke, J.-S. (2009), Mostly Harmless Econometrics -- An Empiricist's Companion, Princeton University Press.

Autor, D. H. & Duggan, M. G. (2003), The Rise in Disability Rolls and the Decline in Unemployment, The Quarterly Journal of Economics, vol. 118 (1), 157-205.

Bhat, C. (2001), Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model, Transportation Research, B 35, 677-693.

Bound, J. (1989), The health and earnings of rejected disability insurance applicants, American Economic Review, vol. 79 (3), 482-503.

Bound, J. & Burkhauser, R. V. (1999), Economic analysis of transfer programs targeted on people with disabilities. In: Ashenfelter, O., Card, D. (Eds.), Handbook of Labor Economics, vol. 3C. North-Holland, Amsterdam.

Burkhauser, R. V., Daly M. C., McVicar D., Wilkins R. (2013), Disability Benefit Growth and Disability Reform in the U.S.: Lessons from Other OECD Nations, Federal Reserve Bank of San Francisco, Working Paper Series.

Bunch, D. (1991), Estimability in the multinomial probit model, Transportation research, B 25, 1-12.

Cai, L. (2010), The relationship between health and labour force participation: Evidence from a panel data simultaneous equation model, Labour Economics, vol. 17(1), 77-90.

Cameron, A. C. & Trivedi, P. K. (2005), Microeconometrics: Methods and Applications, First edition. Cambridge University Press, 516-519.

Campolieti, M. (2004), Disability Insurance Benefits and Labor Supply: Some Additional Evidence, Journal of Labor Economics, vol. 22 (4), 863-889.

Cappellari, L. & Jenkins, S. P. (2006), Calculation of multivariate normal probabilities by simulation with applications to maximum simulated likelihood estimation, IZA Discussion Paper, No. 2112.

Chen, S. & Van der Klaauw, W. (2008), The work disincentive effects of the disability insurance program in the 1990s, Journal of Econometrics, vol. 142, 757-784.

De Jong, P., Lindeboom, M., Van der Klaauw, B. (2010), Screening Disability Insurance Applications, Journal of the European Economic Association, forthcoming.

Federal Social Insurance Office (FSIO) (2014), Statistiken zur Sozialen Sicherheit, IV-Statistik 2013: urlhttp://www.bsv.admin.ch/dokumentation/zahlen/00095/00442/ newline (accessed today)

Federal Social Insurance Office (FSIO) (2013), Merkblätter, 4.01 - Leistungen der IV: newline urlhttp://www.ahv-iv.info/andere/00134/00186/index.html?lang=de newline (accessed today)

Federal Social Insurance Office (FSIO) (2013), Merkblätter, 4.06 - Das IV-Verfahren: newline urlhttp://www.ahv-iv.info/andere/00134/00186/index.html?lang=de newline (accessed today)

Gastwirth, J. L. (1972), On the decline of male labor force participation, Monthly Labor Review, vol. 95 (10), 44-46.

Geweke, J. (1991), Efficient simulation from multivariate normal and Student-t distributions subject to linear constraints, in E. M. Keramidas, ed., Computer Science and Statistics: Proceedings of the Twenty-Third Symposium on the Interface, Interface Foundation of North America, Inc., Fairfax, 571-578.

Geweke, J., Keane M., Runkle D. (1994), Alternative computational approaches to inference in the multinomial probit model, The review of economics and statistics, 609-632.

Gouriéroux Ch. & Monfort A. (1991), Simulation Based Inference in Models with Heterogeneity, Annales d'Économie et de Statistique, vol. 20/21, pp. 69-107.

Gruber, J. (2000), Disability Insurance Benefits and Labor Supply, Journal of Political Economy, vol. 108 (6), 1162-1183.

Gruber, J., Kubik, J. D. (1997), Disability Insurance Rejection Rates and the Labor Supply of Older Workers, Journal of Public Economics, vol. 64, 1-23.

Hajivassiliou, V., McFadden, D., Ruud, P. (1994), Simulation of multivariate normal rectangle probabilities and their derivatives: Theoretical and computational results, Journal of Econometrics, vol. 72, 85-134.

Hajivassiliou, V. & McFadden, D. (1998), The Method of Simulated Scores for the Estimation of LDV Models, Econometrica, vol. 66, 863-896.

Hammersley, J. & Morton, K. (1956), A new Monte Carlo technique: Antithetic variates, Proceedings of the Cambridge Philosophical Society, vol. 52, 449-474.

Karlström, A. M. P. & Svensson, I. (2008), The Employment Effect of Stricter Rules for Eligibility for DI: Evidence from a Natural Experiment in Sweden, Journal of Public Economics, Vol. 92 (10-11), 2071-2082.

Keane, M. (1990), Four essays in empirical macro and labor economics, PhD Thesis, Brown University.

Keane, M. (1992), A note on identification in the multinomial probit model, Journal of Business and Economics Statistics, vol. 10 (2), 193-200.

Keane, M. (1994), A computationally practical simulation estimator for panel data, Econometrica, vol. 62, 95-116. Lee, D. S. & Lemieux, T. (2009), Regression Discontinuity Designs in Economics, National Bureau of Economic Research, No. w14723.

Marschak, J. (1960), Binary choice constraints on random utility indications, in K. Arrow, Stanford Symposium on Mathematical Methods in the Social Sciences. Standford University Press, 312-329.

Miranda, A. & Rabe-Hesketh, S. (2006), Maximum likelihood estimation of endogenous switching and sample selection models for binary, ordinal, and count variables, Stata Journal, vol. 6 (3), 285-308.

McCrary, J. (2008), Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test, Journal of Econometrics, February 2008, 142 (2), 698-714.

OECD (2009), OECD Employment Outlook, Pathways onto (and off) Disability Benefits: Assessing the Role of Policy and Individual Circumstances. OECD Publishing.

OECD (2010), Sickness, Disability and Work: Breaking the Barriers - A Synthesis of Findings across OECD countries. Paris. OECD Publishing.

Roodman, D. (2011), Fitting Fully Observed Recursive Mixed-Process Models with cmp, Stata Journal, vol. 11 (2), 159-206.

Staubli, S. (2011), The impact of stricter criteria for disability insurance on labor force participation, Journal of Public Economics, vol. 95 (9-10), 1223-1235.

Stock, J. H. & Yogo, M. (2005), Testing for weak instruments in linear IV regression, National Bureau of Economic Research, NBER Technical Working Paper No. 284.

Swisher, I. G. (1973), The disabled and the decline in men's labor force participation, Monthly Labor Review, vol. 96 (11), 53.

Train, E. K. (2009), Discrete Choice Methods with Simulation, Second Edition. Cambridge University Press.