Optimal income taxation with spillovers from employer learning Ashley C. Craig
By: Craig, Ashley C
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Item type | Current location | Home library | Call number | Status | Date due | Barcode |
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Artículos | IEF | IEF | OP 2135/2023/2-1 (Browse shelf) | Available | OP 2135/2023/2-1 |
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OP 2135/2023/1-1 Tax audits as scarecrows | OP 2135/2023/1-2 Implications of tax loss asymmetry for owners of S corporations | OP 2135/2023/2 American Economic Journal : Economic Policy | OP 2135/2023/2-1 Optimal income taxation with spillovers from employer learning | OP 2135/2023/2-2 Pensions and fertility | OP 2135/2023/2-3 Taxing billionaires | OP 2135/2023/2-4 Externalities in international tax enforcement |
Resumen.
I study optimal income taxation when human capital investment is imperfectly observable by employers. In the model, Bayesian inference about worker productivity compresses the wage distribution, lowering the private return to human capital investment. An externality arises: given the same information, employers are more optimistic about each individual if workers are generally more productive. The significance of this externality hinges on the accuracy of employers' beliefs and the responsiveness of human capital. For the United States, taking it into account lowers optimal marginal tax rates for most workers, reducing them by a maximum of 9–13 percentage points between $50,000 and $100,000.
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