How can we quickly and accurately measure the macroeconomic shock brought about by COVID-19? Elias Papaioannou, Professor of Economics at London Business School and Academic Director of the Wheeler Institute for Business and Development was joined in conversation with Paolo Surico, Professor of Economics at London Business School, to discuss the economic impact of the COVID-19 pandemic.
- Economists are reliant on household consumption data to provide insights related to the impact of the pandemic, but national statistics are delayed, limiting their utility during the crisis;
- Using anonymized FinTech data, it is possible to analyse income and consumption patterns for a large sample of households alongside the various policy decisions within days;
- Data showed consumption declined in advance of strict social distancing and lockdown measures, indicating fear related to the virus itself drove household spending down;
- There is an imbalance to which sectors have been hardest hit; governments should take a sector-specific rather than blanket approach;
- Both income and consumption inequalities are being exacerbated, with those in the lowest distribution of income having to cut-back on spending, with implications on their ability to buy necessity goods;
- Economists and policymakers have an even greater challenge obtaining high-quality, timely data in emerging economies, where the crisis is becoming even more pressing.
Policymakers need accurate and instantaneous information to inform decisions
The crisis is testing our ability to obtain data, whether it be testing for the virus, but also the diffusion of the macroeconomic shock. Central Banks and Governments typically use data that has a time-lag of several months to shape policy decisions; this is not an optimal situation in a fast-moving crisis of the magnitude we are experiencing. Therefore, Surico has identified opportunities to look at household consumption in real-time, through analysis of FinTech data and transaction data to aggregate household spending to inform macroeconomic policy.
By looking at users of Money Dashboard, Surico can access information on consumption across multiple bank accounts and credit cards for 40,000 households. This has enabled him to look at transaction data within days rather than months, unlike national statistics that are published quarterly, with several months of delay.
Surico also uses his research to demonstrate that while the pandemic has caused both a supply and demand shock, consumption has dropped much more, and much earlier, than income. Surico believes that this is an effect from people observing how the crisis developed in Italy and China and anticipating measures in the UK, even before the government made an official announcement.
Fear and uncertainty had a greater impact than lockdown policies themselves
The drop in discretionary spending observed by Surico is of the magnitude of 30% to 50%. Moreover, this trend occurred in advance of lockdown measures, indicating that concerns about the virus had a significant impact on consumption, rather than policies themselves. This has important ramifications on decisions relating to taking the population out of lockdown, as opening up the economy may not have the desired effect if people are still reluctant to return to normal activity because they are afraid of contracting the virus.
While to date governments have adopted blanket measures across the whole population, Surico’s investigation shows that some sectors are suffering more than others. The shock the economy is facing is random but imbalanced, which leads Surico to question whether Government’s should attempt to cross-subsidize across sectors compensating the losers from the situation from the winners. Similarly, should the government incentives people to move to sectors where there is greater demand. This intersectoral reallocation can be seen by looking at income flows in bank account data. The normal distribution of income is asymmetric, but during the crisis, the proportion of people experiencing a fall in income far outweighs those who are experiencing an increase, with an average decline of £1,000, or 30%. Furthermore, more people are dependent on their overdraft and applying for mortgage payment holidays.
Inequalities are amplified by the crisis, with the lowest earners hit hardest
Pre-crisis, the wealthiest 10% were consuming 2.7x the value of consumption of the bottom 10%; by the end of April, this had increased to 3.2. This trend was similar for income inequality, which has also widened since the crisis started. Weekly consumption data shows those at the bottom of the income distribution have to cut their consumption by more than those at the top, which is important as those people are the ones who have the highest proportion of their consumption as necessity goods. Similarly, the rich are able to accumulate savings by cutting consumption, whereas the poorest are accumulating debt.
Those at the bottom of the income distribution have a savings rate close to zero, meaning they consume most of what they earn. Once the crisis hit, their savings have gone into negative territory because their income has declined by even more than their consumption, so they have to rely on credit or savings to provide necessity goods. This is in stark contrast to those at the top of the income distribution, who have cut back on consumption of non-necessary goods, and therefore their savings have increased.
Not only can Surico identify the income bracket that is most affected by the crisis, through his research he can provide a heat map of the UK region by region, postcode by postcode of where the most severe impact has taken place, providing valuable information for policymakers are they consider more targeted support for people during the crisis.
Governments need to access more financial data so insights can be refined and policy decisions better informed
Surico believes governments need to expand the sample of households that researchers can access to develop insights and trends that economists have greater certainty are representative of the population. He also wants to be able to access data from corporations, so that the government can analyse how businesses are being impacted. He wants to be able to access similar data on corporate spending as he has for households.
The need for data in emerging economies will be even starker
It is clear that the crisis will have an impact that is an order of magnitude greater for developing economies. Surico stresses that the challenge of accessing timely indicators of consumption in countries where national statistics are much less accurate becomes even more acute. He suggests that researchers will need to access mobile payment data, for example, to discover the larger, more eminent and more pressing crisis that is taking place in emerging markets and low-income economies.
Elias Papaioannou’s conversation with Paolo Surico is part of the Wheeler Institute’s COVID-19 series – bringing together the expertise and experience of our extended community to understand, illuminate and offer solutions to the challenges created by COVID-19. Our differentiating factor is the role of business in addressing these challenges, with a focus on the implications and actions for those in developing countries.
If you’re interested in following the Wheeler Institute COVID-19 series, check out our previous episode below.
Elias Papaioannou is academic director of the Wheeler Institute for Business and Development and professor of economics at London Business School, focusing on international finance, political economy, applied econometrics and growth and development.
Paolo Surico is Professor of Economics and Academic Director, Leadership Programmes at London Business School. Paolo’s main research interests are in macroeconomics, fiscal policy and monetary economics. His work has been recently published in leading international academic journals and he has worked as an external consultant for the European Central Bank. He is a Research Affiliate at the Centre for Economic Policy Research and an academic consultant at the Bank of England.