IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v179y2016i4p1051-1067.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssa.12156
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    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, N.B. & Lindeboom, M., 2008. "Does Retirement Kill You? Evidence from Early Retirement Windows," Other publications TiSEM 749af81e-10f6-4c32-b9ae-0, Tilburg University, School of Economics and Management.
    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, May.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kolodziej, Ingo W.K. & García-Gómez, Pilar, 2019. "Saved by retirement: Beyond the mean effect on mental health," Social Science & Medicine, Elsevier, vol. 225(C), pages 85-97.
    2. Matteo Picchio & Jan C. van Ours, 2020. "Mental Health Effects of Retirement," De Economist, Springer, vol. 168(3), pages 419-452, September.
    3. Mattia Filomena & Matteo Picchio, 2023. "Retirement and health outcomes in a meta‐analytical framework," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1120-1155, September.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fe, Eduardo & Hollingsworth, Bruce, 2012. "Estimating the eect of retirement on mental health via panel discontinuity designs," MPRA Paper 38162, University Library of Munich, Germany.
    2. 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.
    3. Mauricio Villamizar‐Villegas & Freddy A. Pinzon‐Puerto & Maria Alejandra Ruiz‐Sanchez, 2022. "A comprehensive history of regression discontinuity designs: An empirical survey of the last 60 years," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1130-1178, September.
    4. Mohamed Ebeid & Umut Oguzoglu, 2023. "Short‐term effect of retirement on health: Evidence from nonparametric fuzzy regression discontinuity design," Health Economics, John Wiley & Sons, Ltd., vol. 32(6), pages 1323-1343, June.
    5. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    6. Quoc-Anh Do & Yen-Teik Lee & Bang Dang Nguyen, 2016. "Directors as Connectors: The Impact of the External Networks of Directors on Firms," Sciences Po publications 52, Sciences Po.
    7. Maja Weemes Grøtting & Otto Sevaldson Lillebø, 2020. "Health effects of retirement: evidence from survey and register data," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(2), pages 671-704, April.
    8. Jin-young Choi & Myoung-jae Lee, 2017. "Regression discontinuity: review with extensions," Statistical Papers, Springer, vol. 58(4), pages 1217-1246, December.
    9. Hiroyuki Motegi & Yoshinori Nishimura & Kazuyuki Terada, 2016. "Does Retirement Change Lifestyle Habits?," The Japanese Economic Review, Japanese Economic Association, vol. 67(2), pages 169-191, June.
    10. Quoc-Anh Do & Yen-Teik Lee & Bang Dang Nguyen, 2016. "Directors as Connectors: The Impact of the External Networks of Directors on Firms," Post-Print hal-03393196, HAL.
    11. Andreas Kuhn & Jean-Philippe Wuellrich & Josef Zweim�ller, 2010. "Fatal attraction? Access to early retirement and mortality," IEW - Working Papers 499, Institute for Empirical Research in Economics - University of Zurich.
    12. Zhu, Rong, 2016. "Retirement and its consequences for women's health in Australia," Social Science & Medicine, Elsevier, vol. 163(C), pages 117-125.
    13. repec:hal:spmain:info:hdl:2441/5q8d3q8agf8hdbs42laqdfujkb is not listed on IDEAS
    14. Nikolov Plamen & Adelman Alan, 2018. "Short-Run Health Consequences of Retirement and Pension Benefits: Evidence from China," Forum for Health Economics & Policy, De Gruyter, vol. 21(2), pages 1-27, December.
    15. Takahide Yanagi, 2014. "The Effect of Measurement Error in the Sharp Regression Discontinuity Design," KIER Working Papers 910, Kyoto University, Institute of Economic Research.
    16. Andrew C. Johnston & Alexandre Mas, 2018. "Potential Unemployment Insurance Duration and Labor Supply: The Individual and Market-Level Response to a Benefit Cut," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2480-2522.
    17. Davezies, Laurent & Le Barbanchon, Thomas, 2017. "Regression discontinuity design with continuous measurement error in the running variable," Journal of Econometrics, Elsevier, vol. 200(2), pages 260-281.
    18. Ning, Manxiu & Gong, Jinquan & Zheng, Xuhui & Zhuang, Jun, 2016. "Does New Rural Pension Scheme decrease elderly labor supply? Evidence from CHARLS," China Economic Review, Elsevier, vol. 41(C), pages 315-330.
    19. Yang He & Otávio Bartalotti, 2020. "Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals [Using Maimonides’ rule to estimate the effect of class size on scholastic achievemen," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 211-231.
    20. Aspen Gorry & Devon Gorry & Sita Nataraj Slavov, 2018. "Does retirement improve health and life satisfaction?," Health Economics, John Wiley & Sons, Ltd., vol. 27(12), pages 2067-2086, December.
    21. Müller, Tobias & Shaikh, Mujaheed, 2018. "Your retirement and my health behavior: Evidence on retirement externalities from a fuzzy regression discontinuity design," Journal of Health Economics, Elsevier, vol. 57(C), pages 45-59.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssa:v:179:y:2016:i:4:p:1051-1067. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.