The increase in the extent of working-from-home determined by the COVID-19 health crisis has led to a substantial shift of economic activity across geographical areas; which we refer to as a Zoomshock. When a person works from home rather than at the office, their work-related consumption of goods and services provided by the locally consumed service industries will take place where they live, not where they work. Much of the clientèle of restaurants, coffee bars, pubs, hair stylists, health clubs, taxi providers and the like located near workplaces is transferred to establishment located near where people live. These data are our calculations of the Zoomshock at the MSOA level. They reflect estimats of the change in the number of people working in UK neighbourhoods due to home-working.The COVID-19 shutdown is not affecting all parts of the UK equally. Economic activity in local consumer service industries (LCSI), such as retail outlets, restaurants, hairdressers, or gardeners has all but stopped; other industries are less affected. These differences among industries and their varying importance across local economies means recovery will be sensitive to local economic conditions and will not be geographically uniform: some neighbourhoods face a higher recovery risk of not being able to return to pre-shutdown levels of economic activity. This recovery risk is the product of two variables. The first is the shock, the effect of the shutdown on local household incomes. The second is the multiplier, the effect on LCSI economic activity following a negative shock to household incomes. In neighbourhoods where many households rely on the LCSI sector as a primary source of income the multiplier may be particularly large, and these neighbourhoods are vulnerable to a vicious circle of reduced spending and reduced incomes. This project will produce data measuring the shock, the multiplier, and the COVID-19 shutdown recovery risk for UK neighbourhoods. These variables will be estimated using individual and firm level information from national surveys and administrative data. The dataset, and corresponding policy report, will be made public and proactively disseminated to guide local and national policy design. Recovery inequality is likely to be substantial: absent intervention, existing regional inequalities may be exacerbated. This research will provide a timely and necessary input into designing appropriate recovery policy.

These data reflect derived variables based on the methodology described in De Fraja, Matheson and Rockey (2021) (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3752977). Variables are derived from 2011 Census data provided through the ONS Nomis website.