We use a model of automation to show that with the current U.S. tax system, a fall in automation costs could lead to a massive rise in income inequality. This inequality can be reduced by raising marginal income tax rates and taxing robots. But this solution involves a substantial efficiency...

We study a model where households make decisions according to a dual-process framework widely used in cognitive psychology. System 1 uses effortless heuristics but is susceptible to biases and errors. System 2 uses mental effort to make more accurate decisions. Through their pricing behavior,...

As remote work opportunities expand, more people are seeking residence in foreign destinations. The resulting surge in foreign residents generates capital gains for property owners but negatively impacts renters and creates potentially important production, congestion, and amenities...

We consider an environment in which there is substantial uncertainty about the potential negative external effects of AI algorithms. We find that subjecting algorithm implementation to regulatory approval or mandating testing is insufficient to implement the social optimum. When testing costs...

We study the immigration policy that maximizes the welfare of the native population in an economy where the government designs an optimal redistributive welfare system and supplies public goods. We show that when the government can design different tax systems for immigrants and natives, free...

Using a quantitative model that features technical progress in automation and endogenous skill choice, we show that, given the current U.S. tax system, a sustained fall in automation costs can lead to a massive rise in income inequality. We characterize the optimal tax system in this model. We...