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Short- and long-run estimates of the local effects of retirement on health

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  • Eduardo Fé
  • Bruce Hollingsworth

Abstract

We explore the existence of short and long term effects of retirement on health. Short term effects are estimated with a regression discontinuity design which is robust to weak instruments and where the underlying assumptions of continuity of potential outcomes are uncontroversial. To identify the long term effects we propose a parametric model which, under strong assumptions, can separate normal deterioration of health from the causal effects of retirement. We apply our framework to the British Household Panel Survey, and find that retirement has little effect on health. However, our estimates suggest that retirement opens the gate to a sedentary life with an impoverished social component and this is a channel through which retirement could indirectly affect health in the long run.
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  • Eduardo Fé & Bruce Hollingsworth, 2016. "Short- and long-run estimates of the local effects of retirement on health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1051-1067, October.
  • Handle: RePEc:bla:jorssa:v:179:y:2016:i:4:p:1051-1067
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    1. Erich Battistin & Agar Brugiavini & Enrico Rettore & Guglielmo Weber, 2009. "The Retirement Consumption Puzzle: Evidence from a Regression Discontinuity Approach," American Economic Review, American Economic Association, vol. 99(5), pages 2209-2226, December.
    2. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    3. David E. Card & David S. Lee & Zhuan Pei & Andrea Weber, 2012. "Nonlinear Policy Rules and the Identification and Estimation of Causal Effects in a Generalized Regression Kink Design," NRN working papers 2012-14, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    4. Bound, John & Stinebrickner, Todd & Waidmann, Timothy, 2010. "Health, economic resources and the work decisions of older men," Journal of Econometrics, Elsevier, vol. 156(1), pages 106-129, May.
    5. Richard Blundell & Costas Meghir & Sarah Smith, 2002. "Pension Incentives and the Pattern of Early Retirement," Economic Journal, Royal Economic Society, vol. 112(478), pages 153-170, March.
    6. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    7. Coe, Norma B. & Lindeboom, Maarten, 2008. "Does Retirement Kill You? Evidence from Early Retirement Windows," IZA Discussion Papers 3817, Institute of Labor Economics (IZA).
    8. Cai, Lixin, 2010. "The relationship between health and labour force participation: Evidence from a panel data simultaneous equation model," Labour Economics, Elsevier, vol. 17(1), pages 77-90, January.
    9. Mazzonna, Fabrizio & Peracchi, Franco, 2012. "Ageing, cognitive abilities and retirement," European Economic Review, Elsevier, vol. 56(4), pages 691-710.
    10. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    11. James Banks & Sarah Smith, 2006. "Retirement in the UK," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 22(1), pages 40-56, Spring.
    12. Feir, Donna & Lemieux, Thomas & Marmer, Vadim, 2014. "Supplement To "Weak Identification in Fuzzy Regression Discontinuity Designs"," Microeconomics.ca working papers vadim_marmer-2014-3, Vancouver School of Economics, revised 02 Mar 2015.
    13. Johnston, David W. & Lee, Wang-Sheng, 2009. "Retiring to the good life? The short-term effects of retirement on health," Economics Letters, Elsevier, vol. 103(1), pages 8-11, April.
    14. Qi Li & Jeffrey Scott Racine, 2006. "Density Estimation, from Nonparametric Econometrics: Theory and Practice," Introductory Chapters, in: Nonparametric Econometrics: Theory and Practice, Princeton University Press.
    15. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    16. Yee Kan, Â Man & Gershuny, Jonathan, 2006. "Infusing time diary evidence into panel data: an exercise in calibrating time-use estimates for the BHPS," ISER Working Paper Series 2006-19, Institute for Social and Economic Research.
    17. Lemieux, Thomas & Milligan, Kevin, 2008. "Incentive effects of social assistance: A regression discontinuity approach," Journal of Econometrics, Elsevier, vol. 142(2), pages 807-828, February.
    18. Guido Imbens & Karthik Kalyanaraman, 2012. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 933-959.
    19. Jonathan Gruber & David A. Wise, 2004. "Social Security Programs and Retirement around the World: Micro-Estimation," NBER Books, National Bureau of Economic Research, Inc, number grub04-1, October.
    20. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    21. Sickles, Robin C & Taubman, Paul, 1986. "An Analysis of the Health and Retirement Status of the Elderly," Econometrica, Econometric Society, vol. 54(6), pages 1339-1356, November.
    22. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    23. Krueger, Alan B & Pischke, Jorn-Steffen, 1992. "The Effect of Social Security on Labor Supply: A Cohort Analysis of the Notch Generation," Journal of Labor Economics, University of Chicago Press, vol. 10(4), pages 412-437, October.
    24. Orme, Chris, 1990. "The small-sample performance of the information-matrix test," Journal of Econometrics, Elsevier, vol. 46(3), pages 309-331, December.
    25. John Bound, 1991. "Self-Reported Versus Objective Measures of Health in Retirement Models," Journal of Human Resources, University of Wisconsin Press, vol. 26(1), pages 106-138.
    26. Disney, Richard & Emmerson, Carl & Wakefield, Matthew, 2006. "Ill health and retirement in Britain: A panel data-based analysis," Journal of Health Economics, Elsevier, vol. 25(4), pages 621-649, July.
    27. John Bound & Timothy Waidmann, 2007. "Estimating the Health Effects of Retirements," Working Papers wp168, University of Michigan, Michigan Retirement Research Center.
    28. Kevin Neuman, 2008. "Quit Your Job and Get Healthier? The Effect of Retirement on Health," Journal of Labor Research, Springer, vol. 29(2), pages 177-201, June.
    29. Lee, David S. & Card, David, 2008. "Regression discontinuity inference with specification error," Journal of Econometrics, Elsevier, vol. 142(2), pages 655-674, February.
    30. Davidson, Russell & MacKinnon, James G., 2010. "Wild Bootstrap Tests for IV Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 128-144.
    31. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    32. Mark Aguiar & Erik Hurst, 2005. "Consumption versus Expenditure," Journal of Political Economy, University of Chicago Press, vol. 113(5), pages 919-948, October.
    33. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    34. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September.
    35. Steven Stern, 1989. "Measuring the Effect of Disability on Labor Force Participation," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 361-395.
    36. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-338, May.
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    4. Hasebe, Takuya & Sakai, Tadashi, 2018. "Are elderly workers more likely to die in occupational accidents? Evidence from both industry-aggregated data and administrative individual-level data in Japan," Japan and the World Economy, Elsevier, vol. 48(C), pages 79-89.
    5. Andreas Kuhn, 2018. "The complex effects of retirement on health," IZA World of Labor, Institute of Labor Economics (IZA), pages 430-430, March.
    6. Salm, Martin & Siflinger, Bettina & Xie, Mingjia, 2021. "The Effect of Retirement on Mental Health: Indirect Treatment Effects and Causal Mediation," Other publications TiSEM e28efa7f-8219-437c-a26d-2, Tilburg University, School of Economics and Management.
    7. Eduardo Fé, 2021. "Pension eligibility rules and the local causal effect of retirement on cognitive functioning," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 812-841, July.
    8. Nielsen, Nick Fabrin, 2019. "Sick of retirement?," Journal of Health Economics, Elsevier, vol. 65(C), pages 133-152.
    9. Jan C. van Ours, 2022. "How Retirement Affects Mental Health, Cognitive Skills and Mortality; An Overview of Recent Empirical Evidence," De Economist, Springer, vol. 170(3), pages 375-400, August.
    10. Leimer, Birgit & van Ewijk, Reyn, 2022. "No “honeymoon phase”: whose health benefits from retirement and when," Economics & Human Biology, Elsevier, vol. 47(C).
    11. Yuanrong Xu, 2023. "The effect of retirement on health and mortality in the United States," Journal of Population Research, Springer, vol. 40(2), pages 1-22, June.

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    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies

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