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Dynamic Analysis and the Economics of Happiness: Rationale, Results and Rules


  • Piper, Alan T.


This paper provides a sustained introduction for the use of dynamic panel methods when analysing life satisfaction. As well as being able to address the issue of serial correlation, dynamic panel analysis also has the advantage of being able to treat variables as exogenous or endogenous, important for happiness, and can generate both contemporaneous and long run estimates for independent variables. A key result found initially for young people, but which is robust to different age ranges and countries, is that happiness is largely contemporaneous although there is a small, persistent effect of the past on current happiness. Additionally, decision rules are provided for the analysis of happiness using dynamic panel analysis.

Suggested Citation

  • Piper, Alan T., 2012. "Dynamic Analysis and the Economics of Happiness: Rationale, Results and Rules," MPRA Paper 43248, University Library of Munich, Germany, revised Dec 2012.
  • Handle: RePEc:pra:mprapa:43248

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    References listed on IDEAS

    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Rafael Di Tella & Robert J. MacCulloch & Andrew J. Oswald, 2003. "The Macroeconomics of Happiness," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 809-827, November.
    3. Blanchflower, David G. & Oswald, Andrew J., 2008. "Is well-being U-shaped over the life cycle?," Social Science & Medicine, Elsevier, vol. 66(8), pages 1733-1749, April.
    4. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    5. Clark, Andrew E & Oswald, Andrew J, 1994. "Unhappiness and Unemployment," Economic Journal, Royal Economic Society, vol. 104(424), pages 648-659, May.
    6. George MacKerron, 2012. "Happiness Economics From 35 000 Feet," Journal of Economic Surveys, Wiley Blackwell, vol. 26(4), pages 705-735, September.
    7. Bottan, Nicolas Luis & Perez Truglia, Ricardo, 2011. "Deconstructing the hedonic treadmill: Is happiness autoregressive?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(3), pages 224-236, May.
    8. Andrew E. Clark & Paul Frijters & Michael A. Shields, 2008. "Relative Income, Happiness, and Utility: An Explanation for the Easterlin Paradox and Other Puzzles," Journal of Economic Literature, American Economic Association, vol. 46(1), pages 95-144, March.
    9. David G. Blanchflower & Andrew Oswald, 2000. "The Rising Well-Being of the Young," NBER Chapters,in: Youth Employment and Joblessness in Advanced Countries, pages 289-328 National Bureau of Economic Research, Inc.
    10. Lelkes, Orsolya, 2008. "Happiness over the life cycle: exploring age-specific preferences," MPRA Paper 7302, University Library of Munich, Germany.
    11. Blanchflower, David G., 2001. "Unemployment, Well-Being, and Wage Curves in Eastern and Central Europe," Journal of the Japanese and International Economies, Elsevier, vol. 15(4), pages 364-402, December.
    12. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    13. David M. Drukker, 2003. "Testing for serial correlation in linear panel-data models," Stata Journal, StataCorp LP, vol. 3(2), pages 168-177, June.
    14. Nattavudh Powdthavee, 2009. "Estimating the Causal Effects of Income on Happiness," Discussion Papers 09/02, Department of Economics, University of York.
    15. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
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    Cited by:

    1. Alan Piper, 2015. "Heaven knows I'm miserable now: overeducation and reduced life satisfaction," Education Economics, Taylor & Francis Journals, vol. 23(6), pages 677-692, December.
    2. Alan Piper, 2015. "Europe’s Capital Cities and the Happiness Penalty: An Investigation Using the European Social Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 123(1), pages 103-126, August.
    3. Chrostek, Pawel, 2013. "An empirical investigation into the determinants and persistence of happiness and life evaluation," MPRA Paper 50442, University Library of Munich, Germany.
    4. Piper, Alan T., 2014. "The Benefits, Challenges and Insights of a Dynamic Panel assessment of Life Satisfaction," MPRA Paper 59556, University Library of Munich, Germany.
    5. Piper, Alan T., 2013. "Happiness, Dynamics and Adaptation," MPRA Paper 52342, University Library of Munich, Germany.
    6. Chrostek, Pawel, 2013. "An empirical investigation into the determinants and persistence of different types of subjective well-being," MPRA Paper 48292, University Library of Munich, Germany.
    7. Piper, Alan T., 2014. "An Investigation into Happiness, Dynamics and Adaptation," MPRA Paper 57778, University Library of Munich, Germany.
    8. Paweł Chrostek, 2016. "An Empirical Investigation into the Determinants and Persistence of Happiness and Life Evaluation," Journal of Happiness Studies, Springer, vol. 17(1), pages 413-430, February.
    9. Piper, Alan, 2013. "A Note on Modelling Dynamics in Happiness Estimations," MPRA Paper 49364, University Library of Munich, Germany.

    More about this item


    Dynamic Panel Analysis; Happiness; Life Satisfaction;

    JEL classification:

    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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