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Working Paper
Optimal taxation with imperfect competition and aggregate returns to specialization
In this paper we explore the proposition that in economies with imperfect competitive markets the optimal capital income tax is negative and the optimal tax on firms profits is confiscatory. We show that if the total factor productivity as well as the measure of firms or varieties are endogenous instead of fixed, then the optimal fiscal policy can lead to different results. The government faces a trade-off between the fixed costs that society pays for the introduction of a new firm and the productivity gains associated to the introduction of a new variety. We find that the optimal fiscal ...
Working Paper
Estate taxation with warm-glow altruism
This article examines the properties of the optimal fiscal policy in an economy with warm-glow altruism (utility interdependence) and heterogeneous individuals. We propose a new efficiency concept, D-efficiency, that considers an implicit constraint in the act of giving: donors cannot bequeath to donees more than their existing resources. Considering this constraint, we show that the market equilibrium is not socially efficient. The efficient level of bequest transfers can be implemented by the market with estate and labor-income subsidies and a capital-income tax. In the absence of lump-sum ...
Working Paper
Indirect taxation and the welfare effects of altruism on the optimal fiscal policy
This paper analyzes the welfare effects of altruism on the optimal fiscal policy. The existence of positive bequests links present and future generations in the economy. We show that these altruistic links provide a new role for indirect taxation (consumption and estate taxes) with important welfare implications. We use three different altruistic approaches (warm-glow, dynastic, and family) to illustrate how the presence of bequests in the budget constraint of the donee gives the government the ability to use indirect taxation to mimic lump-sum taxation and to implement the first-best outcome ...