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Well-Being and Ill-Being: A Bivariate Panel Data Analysis

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  • Lee, Wang-Sheng

    ()
    (Deakin University)

  • Oguzoglu, Umut

    ()
    (University of Manitoba)

Abstract

The aim of this paper is to estimate in a multivariate context the factors associated with well-being and ill-being without making the assumptions that they are opposite ends of the same continuum, and that the factors uniformly affect both well-being and ill-being. Using the first five waves of panel data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, we jointly model positive and negative well-being in a two-equation dynamic panel data model. We found that while past ill-being had significant effect on current well-being there was no support for a reverse relationship (i.e. lagged effect of well-being on current ill-being). In addition, we also found support for asymmetry in how certain factors affect well-being and ill-being. The implication of the findings in this paper for the happiness literature is that for future empirical work, it would perhaps more prudent to begin with the notion that well-being and ill-being are distinct dimensions, that the unobservables that affect well-being and ill-being are correlated, and to specify econometric models that allow for these concepts to be reflected.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3108.

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Length: 24 pages
Date of creation: Oct 2007
Date of revision:
Handle: RePEc:iza:izadps:dp3108

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Keywords: well-being; happiness; ill-being; dynamic panel models; bivariate probit;

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  1. Rob Alessie & Stefan Hochguertel & Arthur van Soest, 2004. "Ownership of Stocks and Mutual Funds: A Panel Data Analysis," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 783-796, August.
  2. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers, Institute for Fiscal Studies W95/17, Institute for Fiscal Studies.
  3. Stefan Boes & Rainer Winkelmann, 2006. "The Effect of Income on Positive and Negative Subjective Well-Being," SOI - Working Papers, Socioeconomic Institute - University of Zurich 0605, Socioeconomic Institute - University of Zurich.
  4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521766555.
  5. Mark Wooden & Bruce Headey, 2004. "The Effects of Wealth and Income on Subjective Well-Being and Ill-Being," Melbourne Institute Working Paper Series, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne wp2004n03, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  6. Rainer Winkelmann, 2005. "Subjective well-being and the family: Results from an ordered probit model with multiple random effects," Empirical Economics, Springer, Springer, vol. 30(3), pages 749-761, October.
  7. Wang-Sheng Lee & Umut Oguzoglu, 2007. "Income Support and Stigma Effects for Young Australians," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 40(4), pages 369-384, December.
  8. Nicole Watson & Mark Wooden, 2004. "The HILDA Survey Four Years On," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 37(3), pages 343-349, 09.
  9. Bruce Headey & Jonathan Kelley & Alex Wearing, 1993. "Dimensions of mental health: Life satisfaction, positive affect, anxiety and depression," Social Indicators Research, Springer, Springer, vol. 29(1), pages 63-82, May.
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