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Generalized Social Marginal Welfare Weights Imply Inconsistent Comparisons of Tax Policies

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  • Itai Sher

    (University of Massachusetts Amherst)

Abstract

This paper concerns Saez and Stantcheva's (2016) generalized social marginal welfare weights (GSMWW), which are used to aggregate losses and gains due to the tax system, while incorporating non-utilitarian ethical considerations. That approach evaluates local changes in tax policy without appealing to a global social objective. However, I argue that local comparisons between different tax systems implicitly entail global comparisons. Moreover, whenever welfare weights are not of a utilitarian kind, these implied global comparisons are inconsistent. Part of the motivation for the GSMWW approach is that it provides a way to incorporate broader ethical judgements into the evaluation of the tax system while preserving the Pareto principle. I suggest that the problems with the approach ought to spark a reconsideration of Pareto if one wants to represent broader values in formal policy analysis.

Suggested Citation

  • Itai Sher, 2021. "Generalized Social Marginal Welfare Weights Imply Inconsistent Comparisons of Tax Policies," Working Papers 2021-009, Human Capital and Economic Opportunity Working Group.
    • Handle: RePEc:hka:wpaper:2021-009
    Note: MIP
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    File URL: http://humcap.uchicago.edu/RePEc/hka/wpaper/Sher_2021_generalized-social-marginal-welfare.pdf
    File Function: First version, February 15, 2021
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    References listed on IDEAS

    as
    1. Fleurbaey,Marc & Maniquet,François, 2011. "A Theory of Fairness and Social Welfare," Cambridge Books, Cambridge University Press, number 9780521715348, September.
    2. Emmanuel Saez & Stefanie Stantcheva, 2016. "Generalized Social Marginal Welfare Weights for Optimal Tax Theory," American Economic Review, American Economic Association, vol. 106(1), pages 24-45, January.
    3. Weinzierl, Matthew, 2014. "The promise of positive optimal taxation: normative diversity and a role for equal sacrifice," Journal of Public Economics, Elsevier, vol. 118(C), pages 128-142.
    4. Kristoffer Berg & Paolo Giovanni Piacquadio, 2020. "The Equal-Sacrifice Social Welfare Function with an Application to Optimal Income Taxation," CESifo Working Paper Series 8505, CESifo.
    5. Marc Fleurbaey & Bertil Tungodden & Howard F. Chang, 2003. "Any Non-welfarist Method of Policy Assessment Violates the Pareto Principle: A Comment," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1382-1386, December.
    6. Emmanuel Saez, 2001. "Using Elasticities to Derive Optimal Income Tax Rates," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(1), pages 205-229.
    7. Sen, Amartya K, 1977. "On Weights and Measures: Informational Constraints in Social Welfare Analysis," Econometrica, Econometric Society, vol. 45(7), pages 1539-1572, October.
    8. Paolo Giovanni Piacquadio, 2017. "A Fairness Justification of Utilitarianism," Econometrica, Econometric Society, vol. 85, pages 1261-1276, July.
    9. Louis Kaplow & Steven Shavell, 2001. "Any Non-welfarist Method of Policy Assessment Violates the Pareto Principle," Journal of Political Economy, University of Chicago Press, vol. 109(2), pages 281-286, April.
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    Cited by:

    1. Louis Kaplow, 2022. "Optimal Income Taxation," NBER Working Papers 30199, National Bureau of Economic Research, Inc.
    2. Erwin Ooghe & Erik Schokkaert & Hannes Serruys, 2023. "Fair Earnings Tax Reforms," CESifo Working Paper Series 10242, CESifo.

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    More about this item

    Keywords

    welfare weights; optimal taxation; utilitarianism; Pareto principle;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies

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