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 alternatively holding developers accountable for adverse external impacts of their algorithms is insufficient to implement the social optimum. When testing costs are low, a combination of mandatory beta testing for external effects and making developers liable for the negative external effects of their algorithms implements the social optimum even when developers have limited liability.
Following the remote-work revolution, more people are seeking residence in foreign destinations. This surge can negatively impact renters and generate important externalities. We study optimal policy towards foreign residents emphasizing the key tradeoffs present in policy discussions. We find that it is not optimal to restrict, tax, or subsidize home purchases by foreign residents.
We address the question of how sensitive is the power of fiscal policy in the ZLB to the assumption of rational expectations. Our analysis weakens the case for using government spending to stabilize the economy when the ZLB binds, but strengthens the case for using tax policy.
Discussion of 'Optimal Monetary Policy with Redistribution' by Jennifer La'O and Wendy Morrison
We study the power of state-dependent unemployment insurance (UI) in stabilizing short-run fluctuations. Managing expectations is key in this application because higher UI generosity raises consumption, partly, by reducing precautionary savings.
Belief disagreement about future income is negatively correlated with economic activity, i.e., unconditionally, the cross-sectional dispersion in expectations is high during recessions. However, I show that the causal impact of economic shocks on disagreement is symmetric around zero, i.e., both positive and negative shocks lead to increases in disagreement. Furthermore, changes to disagreement occur even absent changes in perceived/subjective uncertainty. To reconcile these facts, I argue theoretically that rising disagreement can act as a negative aggregate-demand shock. This mechanism implies that disagreement affects economic activity negatively. The main argument works via the effect of heterogeneous expectations on consumption and savings decisions in the presence of borrowing constraints. Then, I show that this model implies that disagreement is an asymmetric propagation mechanism that amplifies recessions and dampens expansions. Turning to policy, I show that this mechanism may also dampen the impact of monetary stimulus policy, while unconventional fiscal policy can still be very effective.
Geographical labor mobility has been a crucial margin of adjustment of the US labor market in response to local shocks. However, migration rates have been steadily declining since the 1990s. Consistent with the literature, I show that this decline is robust across various socioeconomic groups and is not driven by composition changes, and it is strongly associated with the observed decline in employment dynamism. Furthermore, I provide novel evidence that the response of migration to local economic shocks has substantially decreased during the same period. I develop a model with heterogeneous workers and locations and argue that rising worker-job specialization can account for these changes. These findings have implications for coordinating stabilization policy in a large monetary union like the US.
I study the origins and consequences of disagreement in expectations about GDP. People are differently exposed to business cycles and so choose different levels of attention to the Macroeconomy. This form of disagreement increases the severity of recessions and changes how the economy responds to monetary and fiscal policies.
We develop a quantitative model of technical progress in automation and endogenous skill choice. We find that it is optimal to tax robots while the current generations of routine workers are active in the labor force. Once these workers retire, optimal robot taxes are zero.
We study how optimal immigration policy interacts with the welfare system. When the welfare system for immigrants and natives can be designed independently, free immigration is optimal. Instead, when they must be treated alike, it may be optimal to ban low-skill immigration and have free immigration for high-skill workers. We calibrate our model and perform optimal policy exercises for the U.S.