Building back with data

Data shows financial support worked during Covid – and can help to target resources as we recover

How do we know if a policy works? It depends who you ask: the people it aims to help? The public in general? The media... social media? For an objective answer, you need data.

As HM Treasury prepared for the March

2021 Budget, their distributional analysis model, which uses Understanding Society data, showed that government interventions were supporting the poorest working households the most as a proportion of pre-Covid income. Earlier analysis, from when the pandemic first hit, showed much the same: the government’s interventions were worth an average of around a fifth of incomes

for working households, and reduced the scale of income losses by up to two-thirds.

Understanding Society, the UK Household Longitudinal Study, interviews tens of thousands of people around the country every year, gathering data on people’s lives on a representative sample of the UK population. In April 2020, we began a new, regular online survey to find out how Covid was affecting people, including their finances. We made the data from the new survey available with information from 2019 pre-pandemic interviews, to make clear comparisons possible.

In January, academics at the Universities of Oxford and Essex, and the European University Institute, used our surveys to show that the economic impact of Covid has been uneven and regressive. Those with precarious employment, under 30 and from minority ethnic groups faced the biggest job disruption – and declines in household earnings were most severe among the lowest earners.

In June, the Bright Blue think tank, also using our data, found that a significant minority of households who were new or existing users of Universal Credit were not up to date with household bills, rent or mortgage payments, were likely to face worsening debt, and were finding it difficult to manage.

As we emerge from the pandemic, and the government’s ‘levelling up’ agenda takes shape, organisations like the Social Mobility Commission will use Understanding Society and other data to understand how people can move both up and down the social scale, and who is affected most, allowing departments to identify where to target limited resources.

Whatever happens, government departments, researchers, civil society organisations and others will always need good quality evidence of the changes policies make in people’s lives. Longitudinal data offers them exactly that.