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Clusters of Attributes and Well-Being in the US

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  • Hirschberg, J.G.
  • Maasoumi, E.
  • Slottje, D.J.

Abstract

Using ARIMA models and entropy, the dynamic evolution of several functions of aggregate income and other attributes of well-being is analyzed for statistical "similarity" in order to determine potentially distinct dimensions in multidimensional analysis of welfare and quality of life in the US. The entropy metric compares entire distributions and is more general than principal components and other correlation-based techniques for clustering. To help macroeconomic policy makers, we compare the distribution of several composite measures of well-being, including income, with the distribution of some common measures of aggregate income over the period 1915-1995.

Suggested Citation

  • Hirschberg, J.G. & Maasoumi, E. & Slottje, D.J., 2001. "Clusters of Attributes and Well-Being in the US," Department of Economics - Working Papers Series 778, The University of Melbourne.
  • Handle: RePEc:mlb:wpaper:778
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    Cited by:

    1. Wiebke Kuklys & Ingrid Robeyns, 2004. "Sens's Capability Approach to Welfare Economics," Papers on Strategic Interaction 2004-03, Max Planck Institute of Economics, Strategic Interaction Group.
    2. Rahman, Tauhidur & Mittelhammer, Ron C. & Wandschneider, Philip R., 2011. "Measuring quality of life across countries: A multiple indicators and multiple causes approach," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(1), pages 43-52, February.
    3. Martin Binder, 2014. "Subjective Well-Being Capabilities: Bridging the Gap Between the Capability Approach and Subjective Well-Being Research," Journal of Happiness Studies, Springer, vol. 15(5), pages 1197-1217, October.
    4. Dalila De Rosa, 2018. "Capability Approach and Multidimensional Well-Being: The Italian Case of BES," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(1), pages 125-155, November.
    5. Paul Makdissi & Quentin Wodon, 2001. "Defining and Measuring (Extreme) Poverty," Cahiers de recherche 04-05, Departement d'Economique de l'École de gestion à l'Université de Sherbrooke, revised 2004.
    6. Esfandiar Maasoumi & Daniel L. Millimet, 2005. "Robust inference concerning recent trends in US environmental quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 55-77, January.
    7. Tauhidur Rahman & Ron C. Mittelhammer & Philip Wandschneider, 2005. "Measuring the Quality of Life Across Countries: a Sensitivity Analysis of Well-Being Indices," WIDER Working Paper Series RP2005-06, World Institute for Development Economic Research (UNU-WIDER).
    8. Wiebke Kuklys, 2004. "Measuring Standard of Living in the UK - An Application of Sen's Functioning Approach Using Structural Equation Models," Papers on Strategic Interaction 2004-11, Max Planck Institute of Economics, Strategic Interaction Group.
    9. Joseph G. Hirschberg & Jenny N. Lye, 2001. "Clustering in a Data Envelopment Analysis Using Bootstrapped Efficiency Scores," Department of Economics - Working Papers Series 800, The University of Melbourne.
    10. Žmuk Berislav, 2015. "Quality of Life Indicators in Selected European Countries: Hierarchical Cluster Analysis Approach," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 1(1-2), pages 42-54, December.
    11. Kuklys, W. & Robeyns, I., 2004. "Sen’s Capability Approach to Welfare Economics," Cambridge Working Papers in Economics 0415, Faculty of Economics, University of Cambridge.
    12. Esfandiar Maasoumi & Le Wang, 2008. "Economic Reform, Growth and Convergence in China," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 128-154, March.
    13. Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
    14. Nesson, Erik T. & Robinson, Joshua J., 2019. "On the measurement of health and its effect on the measurement of health inequality," Economics & Human Biology, Elsevier, vol. 35(C), pages 207-221.
    15. Nesson, Erik T. & Robinson, Joshua J., 2015. "An information theory based framework for the measurement of population health," Economics & Human Biology, Elsevier, vol. 17(C), pages 86-103.
    16. Roma Debnath & Ravi Shankar, 2014. "Does Good Governance Enhance Happiness: A Cross Nation Study," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 116(1), pages 235-253, March.

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    More about this item

    Keywords

    Time Series; Information Measures; Aggregate Well-being; Entropy;
    All these keywords.

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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