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A Note on Modelling Dynamics in Happiness Estimations

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  • Piper, Alan

Abstract

This short note discusses two alternative ways to model dynamics in happiness regressions. A explained, this may be important when standard fixed effects estimates have serial correlation in the residuals, but is also potentially useful when serial correlation is not a problem for providing new insights in the happiness of economics area. The note discusses modelling dynamics two ways the note discusses are via a lagged dependent variable, and via an AR(1) process. The usefulness and statistical appropriateness of each is discussed with reference to happiness. Finally, a flow chart is provided summarising key decisions regarding the choice regarding, and potential necessity of, modelling dynamics.

Suggested Citation

  • Piper, Alan, 2013. "A Note on Modelling Dynamics in Happiness Estimations," MPRA Paper 49364, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:49364
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    File URL: https://mpra.ub.uni-muenchen.de/49709/23/MPRA_paper_49709.pdf
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    References listed on IDEAS

    as
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    2. David Blanchflower & Andrew Oswald & Sarah Stewart-Brown, 2013. "Is Psychological Well-Being Linked to the Consumption of Fruit and Vegetables?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(3), pages 785-801, December.
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    4. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
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    6. 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.
    7. Piper, Alan T., 2012. "A Happiness Test of Human Capital Theory," MPRA Paper 43496, University Library of Munich, Germany.
    8. Blanchflower, David G; Oswald, Andrew, 2011. "International Happiness," CAGE Online Working Paper Series 39, Competitive Advantage in the Global Economy (CAGE).
    9. David M. Drukker, 2003. "Testing for serial correlation in linear panel-data models," Stata Journal, StataCorp LP, vol. 3(2), pages 168-177, June.
    10. McGuirk, Anya M. & Spanos, Aris, 2004. "Revisiting Error Autocorrelation Correction: Common Factor Restrictions And Granger Causality," 2004 Annual meeting, August 1-4, Denver, CO 20176, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
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    12. Bichaka Fayissa & Shah Danyal & J.S. Butler, 2011. "The Impact of Education on Health Status: Evidence from Longitudinal Survey Data," Working Papers 201101, Middle Tennessee State University, Department of Economics and Finance.
    13. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    14. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    15. David G. Blanchflower & Andrew J. Oswald, 2011. "International Happiness," NBER Working Papers 16668, National Bureau of Economic Research, Inc.
    16. David Roodman, 2006. "How to Do xtabond2," North American Stata Users' Group Meetings 2006 8, Stata Users Group.
    17. 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.
    18. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    Cited by:

    1. Piper, Alan T., 2013. "Happiness, Dynamics and Adaptation," MPRA Paper 52342, University Library of Munich, Germany.
    2. 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.
    3. Piper, Alan T., 2014. "Sliding down the U-shape? An investigation of the age-well-being relationship, with a focus on young adults," MPRA Paper 55819, University Library of Munich, Germany.
    4. Christiana Charalambidou & Steven McIntosh, 2021. "Over‐education in Cyprus: Micro and macro determinants, persistence and state dependence. A dynamic panel analysis," Manchester School, University of Manchester, vol. 89(2), pages 172-189, March.
    5. Piper, Alan T., 2014. "An Investigation into Happiness, Dynamics and Adaptation," MPRA Paper 57778, University Library of Munich, Germany.

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    More about this item

    Keywords

    Happiness; Dynamics; Lagged Dependent Variable; AR(1) process; Estimation;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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