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Doubling Up: A Gift or a Shame? Multigenerational Households and Parental Depression of Older Europeans

Author

Listed:
  • Luis Aranda

    (Department of Economics, University Of Venice C� Foscari)

Abstract

The Great Recession has brought along a rearrangement of living patterns both in the U.S. and in Europe. This study seeks to identify the consequences of the �doubling up� of two or more generations of adults into the same household. In particular, a difference-in-difference (DID) propensity score matching approach is employed to target the causal effect of a change in geographical closeness of respondents and their children �either moving together (doubling up) or apart (splitting up)� on the well-being of the older generation, proxied by their depression score. We find that, although heterogeneous across European regions, in no case does doubling up pose a negative effect to the quality of life of older Europeans. The opposite is true for central and southern Europe, where a double up seems to be followed by a significant reduction in the depression level of the older generation. Our results highlight that, although a negative connotation has usually been attached to multigenerational living arrangements in the post-WWII era, its benefits are evident and, in a time marked by increasing demographic aging, can lead to significant improvements in the quality of life of older Europeans.

Suggested Citation

  • Luis Aranda, 2013. "Doubling Up: A Gift or a Shame? Multigenerational Households and Parental Depression of Older Europeans," Working Papers 2013:29, Department of Economics, University of Venice "Ca' Foscari", revised 2013.
  • Handle: RePEc:ven:wpaper:2013:29
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    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. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    3. Ruhm, Christopher J., 2005. "Healthy living in hard times," Journal of Health Economics, Elsevier, vol. 24(2), pages 341-363, March.
    4. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    5. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    6. Sourafel Girma & Holger Görg, 2016. "Evaluating the foreign ownership wage premium using a difference-in-differences matching approach," World Scientific Book Chapters, in: MULTINATIONAL ENTERPRISES AND HOST COUNTRY DEVELOPMENT Volume 53: World Scientific Studies in International Economics, chapter 2, pages 17-32, World Scientific Publishing Co. Pte. Ltd..
    7. Black, Dan A. & Smith, J.A.Jeffrey A., 2004. "How robust is the evidence on the effects of college quality? Evidence from matching," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 99-124.
    8. Greg Kaplan, 2012. "Moving Back Home: Insurance against Labor Market Risk," Journal of Political Economy, University of Chicago Press, vol. 120(3), pages 446-512.
    9. Juan M. Villa, 2009. "DIFF: Stata module to perform Differences in Differences estimation," Statistical Software Components S457083, Boston College Department of Economics, revised 31 Dec 2019.
    10. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    11. Christopher J. Ruhm, 2000. "Are Recessions Good for Your Health?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(2), pages 617-650.
    12. Jeffrey Smith, 2000. "A Critical Survey of Empirical Methods for Evaluating Active Labor Market Policies," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 136(III), pages 247-268, September.
    13. 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.
    14. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-318, May.
    15. Ruhm, Christopher J., 2003. "Good times make you sick," Journal of Health Economics, Elsevier, vol. 22(4), pages 637-658, July.
    16. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    17. Michael Lechner, 2002. "Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 59-82, February.
    18. Lee, David S., 2008. "Randomized experiments from non-random selection in U.S. House elections," Journal of Econometrics, Elsevier, vol. 142(2), pages 675-697, February.
    19. Meyer, Bruce D, 1995. "Natural and Quasi-experiments in Economics," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 151-161, April.
    20. John DiNardo & Justin L. Tobias, 2001. "Nonparametric Density and Regression Estimation," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 11-28, Fall.
    21. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    22. Richard Blundell & Monica Costa Dias, 2000. "Evaluation methods for non-experimental data," Fiscal Studies, Institute for Fiscal Studies, vol. 21(4), pages 427-468, January.
    23. Douglas L. Miller & Marianne E. Page & Ann Huff Stevens & Mateusz Filipski, 2009. "Why Are Recessions Good for Your Health?," American Economic Review, American Economic Association, vol. 99(2), pages 122-127, May.
    24. Bryson, Alex & Dorsett, Richard & Purdon, Susan, 2002. "The use of propensity score matching in the evaluation of active labour market policies," LSE Research Online Documents on Economics 4993, London School of Economics and Political Science, LSE Library.
    25. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    26. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    27. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
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    More about this item

    Keywords

    Doubling up; Depression; Aging; Difference-in-differences; Matching estimator;
    All these keywords.

    JEL classification:

    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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