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Abstract:

This paper develops a novel machine learning based approach to study time consistent optimal taxation in a heterogeneous agent model with aggregate uncertainty. The findings reveal that optimal fiscal policy differs significantly between heterogeneous and representative agent models, with the government's taxation decisions being influenced by the asset distribution and inequality dynamics. The results highlight the importance of considering household heterogeneity when designing fiscal policies, as optimal tax rates respond to changes in the asset distribution and aggregate shocks.

To further the goal of having a social discussion, the Department will buy the first round of appetizers at Inner Rail at 4:30PM

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  • Audrey Vega

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