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Semi-parametric Models for Satisfaction with Income

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  • Bellemare, C.

    (Tilburg University, School of Economics and Management)

  • Melenberg, B.

    (Tilburg University, School of Economics and Management)

  • van Soest, A.H.O.

    (Tilburg University, School of Economics and Management)

Abstract

An overview is presented of some parametric and semi-parametric models, estimators, and specification tests that can be used to analyze ordered response variables. In particular, limited dependent variable models that generalize ordered probit are compared to regression models that generalize the linear model. These techniques are then applied to analyze how self-reported satisfaction with household income relates to household income, family composition, and other background variables. Data are drawn from the 1998 wave of the German Socio- Economic Panel. The results are used to estimate equivalence scales and the cost of children. We find that the standard ordered probit model is rejected, while some semi-parametric specifications survive specification tests against nonparametric alternatives. The estimated equivalence scales, however, are often similar for the parametric and semi-parametric specifications.
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Suggested Citation

  • Bellemare, C. & Melenberg, B. & van Soest, A.H.O., 2002. "Semi-parametric Models for Satisfaction with Income," Other publications TiSEM a7ab8987-444a-4ab0-b566-c, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:a7ab8987-444a-4ab0-b566-c21bd31f48b0
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    Citations

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    Cited by:

    1. Ralf A. Wilke, 2006. "Semi-parametric estimation of consumption-based equivalence scales: the case of Germany," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 781-802.
    2. 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.
    3. Stefan Boes, 2013. "Nonparametric analysis of treatment effects in ordered response models," Empirical Economics, Springer, vol. 44(1), pages 81-109, February.
    4. Christian Dudel & Notburga Ott & Martin Werding, 2013. "Maintaining One's Living Standard at Old Age - What Does That Mean?: Evidence Using Panel Data from Germany," SOEPpapers on Multidisciplinary Panel Data Research 563, DIW Berlin, The German Socio-Economic Panel (SOEP).
    5. Stanislaw Maciej Kot, 2023. "Equivalence scales for continuous distributions of expenditure," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 18(1), pages 185-218, March.
    6. Dustmann C. & Van Soest A., 2004. "An Analysis of Speaking Fluency of Immigrants Using Ordered Response Models With Classification Errors," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 312-321, July.
    7. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    8. Dudel Christian & Garbuszus Jan Marvin & Ott Notburga & Werding Martin, 2017. "Matching as Non-Parametric Preprocessing for the Estimation of Equivalence Scales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(2), pages 115-141, April.
    9. Christian Dudel & Julian Schmied, 2019. "Pension adequacy standards: an empirical estimation strategy and results for the United States and Germany," MPIDR Working Papers WP-2019-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    10. Martin Biewen & Andos Juhasz, 2017. "Direct Estimation of Equivalence Scales and More Evidence on Independence of Base," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 875-905, October.
    11. Stefan Boes & Rainer Winkelmann, 2006. "Ordered response models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 167-181, March.
    12. Connor, Gregory & Flavin, Thomas, 2015. "Strategic, unaffordability and dual-trigger default in the Irish mortgage market," Journal of Housing Economics, Elsevier, vol. 28(C), pages 59-75.
    13. Wiebke Kuklys, 2004. "A Monetary Approach to Capability Measurement of the Disabled - Evidence from the UK," Papers on Strategic Interaction 2004-08, Max Planck Institute of Economics, Strategic Interaction Group.
    14. Mark B. Stewart, 2009. "The Estimation Of Pensioner Equivalence Scales Using Subjective Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(4), pages 907-929, December.
    15. Christian Dudel & Jan Marvin Garbuszus & Notburga Ott & Martin Werding, 2014. "Non-Parametric Preprocessing for the Estimation of Equivalence Scales," CESifo Working Paper Series 5103, CESifo.
    16. Kuklys, W. & Robeyns, I., 2004. "Sen’s Capability Approach to Welfare Economics," Cambridge Working Papers in Economics 0415, Faculty of Economics, University of Cambridge.
    17. Christian Dudel & Jan Marvin Garbuszus & Julian Schmied, 2021. "Assessing differences in household needs: a comparison of approaches for the estimation of equivalence scales using German expenditure data," Empirical Economics, Springer, vol. 60(4), pages 1629-1659, April.
    18. Christian Dudel & Notburga Ott & Martin Werding, 2016. "Maintaining one’s living standard at old age: What does that mean?," Empirical Economics, Springer, vol. 51(3), pages 1261-1279, November.
    19. Gregory Connor & Thomas Flavin, 2013. "Irish Mortgage Default Optionality," Economics Department Working Paper Series n243-13.pdf, Department of Economics, National University of Ireland - Maynooth.
    20. Biewen, Martin & Juhasz, Andos, 2013. "A Goodness-of-Fit Approach to Estimating Equivalence Scales," IZA Discussion Papers 7209, Institute of Labor Economics (IZA).

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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