NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Generalized Social Marginal Welfare Weights for Optimal Tax Theory

Emmanuel Saez, Stefanie Stantcheva

NBER Working Paper No. 18835
Issued in February 2013
NBER Program(s):   PE

This paper proposes a theory of optimal taxation using the tax reform approach and generalized social marginal welfare weights to capture social preferences for redistribution. A tax system is optimal if no budget neutral small reform can increase a weighted sum of (money metric) gains and losses across individuals. However, the weights used for aggregating gains and losses are not derived from a standard social welfare function based on individual utilities but instead directly specified to reflect society's views for justice. Optimum tax formulas take the same form as standard welfarist tax formulas by simply substituting standard marginal social welfare weights with those generalized marginal social welfare weights. We show how the use of suitable generalized social welfare weights can help resolve most of the puzzles of the traditional welfarist approach while retaining constrained Pareto efficiency. In contrast to the welfarist approach, generalized welfare weights can be specified to (1) provide a rich theory of optimal taxation even absent any behavioral responses, (2) treat differently ``deserved income'' vs. ``undeserved income,'' (3) treat differently ``deserving transfer beneficiaries'' vs. ``free loaders'', (4) rule out the use of tags unless they can make a Pareto improvement. We show how the most prominent alternatives to utilitarianism such as Libertarianism, Rawlsianism, Equality of Opportunity, Fair Income Taxation, Poverty alleviation, can be re-cast within our theory. Hence, generalized welfare weights can be derived from social justice principles, leading to a normative theory of taxation. Generalized welfare weights can also be derived from estimating actual social preferences of the public, leading to a positive theory of taxation. We use a simple online survey to illustrate this latter approach.

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