Who Gains, Who Bears the Shock, and What Policy Can Do

The spatial changes created by full-time WFH are not shared evenly. This chapter examines how portability distributes welfare, local-shock exposure, tax revenue, and the benefits of relocation subsidies across remote-capable workers, always-commuters, and cities. The practical judgment is twofold: identify who gains from the option to move or stay employed across a shock, and evaluate a policy by the additional choices it creates rather than by the number of people it pays.

Portability creates uneven welfare

The Dallas Fed model measures welfare with a consumption-equivalent change: the percentage change in consumption and housing that would make a worker indifferent between the original environment and the WFH transition. It is not a survey score and not a complete measure of social welfare. It is a way to compare how much the modeled change in jobs, rents, locations, and employment risk is worth to different workers.

The distribution is sharply uneven. The average gain across all workers is 0.72%, but almost all of it accrues to remote-capable workers, whose average gain is 1.96%. Always-commuters are essentially unchanged on average. That overall average would conceal the central result if it were reported alone: the value of WFH comes mainly from giving some workers access to a national labor market and the ability to change residence without immediately ending a job.

The largest gains go to remote-capable workers who were in commuter jobs just before the shock, particularly those living in large cities. These workers receive a new option at the moment when it is most valuable. They may move from a high-rent city while retaining a relatively strong wage, or they may accept a remote job that gives them access to a wider set of employers. Their gain combines several channels: the amenity of remote work, access to a national remote wage distribution, lower housing costs after relocation, and a better match between the worker’s preferred location and the place where they live.

Workers who were already in remote jobs gain less on average because they already had the central option. They can still benefit from a higher chance of finding another remote job after a separation, but they do not receive the same immediate change in job status. Unemployed remote-capable workers also gain because their probability of receiving a remote offer rises. The timing of the initial job therefore matters: a remote-capable commuter in a large, expensive city is positioned differently from a remote worker who already lives in a low-rent city or an always-commuter whose job cannot travel.

Always-commuters experience smaller average effects, but the sign varies by place. In small cities, the arrival of remote-capable workers raises housing demand and rents, which can reduce the welfare of commuters who remain. In large cities, remote-capable out-migration lowers rents, allowing always-commuters to gain modestly even though they do not receive a portable job. A city’s average effect can therefore look close to zero while the distribution inside the city changes considerably.

The gains are also limited by the cost of reaching the new equilibrium. A static comparison might treat a worker as if they could instantly choose a high-value remote job and a low-rent home. The dynamic model instead requires the worker to search, pay moving costs, wait for the right employment state, and live through price adjustment. When the model evaluates workers in the states they are expected to reach after reallocation, welfare gains are almost 40% higher than when it evaluates them from their original states. The difference measures the cost of beginning in the old location and employment state and having to make the transition.

That transition cost is not a minor detail.