The restrictions put in place to slow the spread of Covid-19 had unequal impacts across society. People in lower-paid jobs were more likely to be affected since many of the sectors in which they work require face-to-face interaction. This had knock-on effects on their spending and wellbeing.
Evidence from past recessions shows that economic downturns affect poor and rich people in different ways, with the poor suffering the most in terms of reductions in consumption, worsening job conditions and declines in general wellbeing.
Data on the first wave of the Covid-19 pandemic indicate that poor people around the world were most affected in terms of their jobs (the labour market downturn). The rich, on the other hand, saw a bigger decrease in their spending. Industries like hospitality, which require face-to-face interactions and employ lower-skilled workers, were hit the hardest.
Was the Covid-19 recession different from previous downturns?
The pandemic affected the world in ways that made it (and continue to make it) starkly different from previous downturns. It brought about a rapid and widespread economic decline, characterised by disruptions to global supply chains, numerous business closures, and reduced consumption and spending due to lockdowns and other social restrictions.
These measures have had a significant influence on the economy, financial markets and the overall functioning of our societies. In addition, the pandemic's severe health implications distinguish it from traditional recessions. The risk of infection, the severity of the illness, and the strain on healthcare systems have added complexity and uncertainty to the overall outlook, surpassing that of typical recessions.
Figure 1 shows that as a result, global uncertainty indices were at their peak during the first wave of the pandemic (January to June 2020). All these elements added to the unique challenges of the Covid-19 recession.
Further, while virtually everyone was economically affected by the pandemic in some way, it is important for policy-makers and individuals to recognise that the impact was not equal across society. Vulnerable and marginalised individuals were disproportionately badly affected, not only in terms of economics but also in areas such as health, education and overall wellbeing (according to a number of studies, including Stancheva, 2022).
Figure 1: World uncertainty index
Source: Ahir et al, 2022
How can we measure the effects of the pandemic?
Having a good measure of the short- and medium-run economic effects of Covid-19, particularly of the first wave, is of primary importance. But it is also very challenging to achieve, both from an empirical and theoretical point of view.
Empirically, during the first wave of the pandemic, there were many other things happening at the same time that could affect any analysis, such as changes in expectations and policy interventions. This makes it problematic to isolate the specific effects of the pandemic itself.
Further, from a theoretical perspective, the pandemic does not easily fit into standard economic analysis, either at the individual level (microeconomic) or at the level of the economy as a whole (macroeconomic). Consequently, analysing the pandemic using existing economic models is difficult.
Facing these challenges, the economic profession quickly provided disaggregated daily or weekly data for the United States and other industrialised economies, either from businesses or related agencies (such as Track the Recovery) or through online daily surveys (Dietrich et al, 2020).
From this, combining US daily economic data and significant financial market movements caused by news about the pandemic, research shows that such pandemic-induced shocks had substantial negative effects on various macroeconomic and financial indicators (Miescu and Rossi, 2021).
For the United States, a pandemic-induced event that leads to a 1% fall in the S&P 500 index – a stock market indicator tracking the performance of the 500 largest companies on the US stock exchange – has a short-run impact on standard economic indicators such as employment (-0.3%), private expenditure (-0.6%) and small business revenues (-0.6%). All these effects are significant and large in magnitude, and the peak effect is between 20 and 30 days after the event (see Figure 2).
Figure 2: Response to a pandemic-induced shock, aggregate variables
Source: Miescu and Rossi, 2021
Note: The Vix is the benchmark index that reports the market’s expectations of future volatility. It is commonly used as a measure of uncertainty.
Were the short-run effects of the pandemic the same across the economy?
The results of the study looking at the US economy as a whole (Miescu and Rossi, 2021) are broadly consistent with the recessionary effects of the first wave of the pandemic typically found in other studies (for example, Baek et al, 2020 and Coibion et al, 2020).
The main benefit of looking at economic data alongside financial market movements is that this approach can be expanded to incorporate the heterogeneous effects of the pandemic alongside the macroeconomic ones in a coherent unified framework. For example, this statistical framework can be used to measure how Covid-19 affected overall employment, as well as its effects on different income groups.
This is particularly important for policy-makers because it is now evident that the impact of the pandemic has varied widely across different parts of the economy – both in terms of people and sectors of the economy (see, for example, Chetty, 2020).
For example, strict lockdown measures have had strong effects on employees working in industries requiring routine face-to-face interactions, such as manufacturing and hospitality. On the other hand, employees in industries that could support remote working, as in the business services sector, were less affected.
Along these lines, two key differences in the effects of the pandemic are particularly crucial for households' behaviour and wellbeing. The first relates to the distribution of income and the disparities between wealthier and poorer regions (Chetty, 2020). The second is the variations between different sectors, such as business services, education and hospitality, as well as expenditure categories, such as food services and transport (see Table 1).
Table 1: Heterogeneous responses to Covid-19
Source: Miescu and Rossi, 2021
Note: The symbols * and ** represent the 68% and 90% significance level.
We start by looking at the employment indicators. During the first wave of the pandemic, employment in US areas with low incomes (the bottom 25%) fell almost twice as much as in high-income areas (the top 25%). Specifically, the decrease was around 0.4% in low-income areas, while it was only 0.23% in high-income areas.
There are a couple of reasons that can explain this finding. First, certain industries, such as business services, tend to have more workers from high-income backgrounds. These industries were able to continue operating during the pandemic because they require less face-to-face contact and employees could work from home. We can see this reflected in the relatively small decrease in revenues for small businesses operating in this sector (see part B of Table 1).
Second, it is natural to expect that high-income workers, who generally have higher skill levels, are less affected by economic ups and downs. This is a common finding in studies of the relationship between the overall economy and employment (such as Bils et al, 2012).
In simpler terms, the analysis shows that employment decreased more in poorer areas compared with richer areas. One possible explanation for this pattern is that certain industries predominantly employing higher-income workers were able to sustain their operations with fewer restrictions during the pandemic. Further, higher-income workers often possess greater skills and are less susceptible to economic fluctuations.
What about consumption? In richer areas, there was a bigger drop in spending than in poorer areas. Specifically, expenditure in high-income areas decreased by around 0.58%, while in poorer areas, the drop was around 0.39% (see Table 1).
There are a couple of reasons that explain this. First, it seems that households with higher incomes rely more on their investments and assets to fund their expenses. When the pandemic first hit, the returns on these investments dropped significantly.
But some evidence also suggests that these households were able to offset this impact to some extent by adjusting their investment portfolios (as shown in a survey conducted by Coibion et al, 2020).
Second, the decrease in spending mostly occurred in categories that were not available during the lockdown, such as restaurants and cafes (food services) and entertainment. These are all activities that are more accessible to wealthier households (see part C of Table 1). On the other hand, poorer households tended to spend relatively more on groceries, the demand for which actually increased during the pandemic.
Businesses and industries
The decline in small businesses opening follows the same pattern as the spending variable (Table 1, part A). These businesses were more severely affected by the pandemic in wealthier areas compared with poorer ones.
Further, Covid-19 also had different effects across US industries (see part B of Table 1). There is a clear pattern that might not come as a surprise. Industries that rely less on face-to-face and personal interactions were less affected by the shocks caused by the pandemic compared with industries that heavily depend on in-person interactions.
For example, the professional and business services industry experienced a smaller decrease in terms of employment, revenues and business openings compared with the leisure and hospitality sector, or education and health services. This finding is specific to the pandemic. Before that, the main factor that determined how businesses responded to economic fluctuations was their financial situation or financial exposure.
These findings are consistent with the descriptive evidence in studies of other countries (Hacioglu et al, 2021, for the UK; Bounie et al, 2020, for France; and Aspachs et al, 2022, for Spain). These analyses find that the largest drop in earnings happened in areas with poorer households, while the biggest reduction in spending was in rich areas.
These studies also report that the effects of the pandemic on business activities depended crucially on how a specific industry relies on in-person interactions (for example, Pagano et al, 2020). The results presented in Miescu and Rossi (2021) are also consistent with the interpretation of the pandemic as a large industry and sector reallocation shock.
In fact, during the first wave of the pandemic, the overall resources of the economy were reallocated towards industries that could function with remote working and away from those sectors relying more on face-to-face interactions (see Barrero et al, 2020).
We are still experiencing many important challenges left by Covid-19, and the response to these is central in current policy and research debates. On this, it will be important to understand the long-run impact of the unequal exposure to the first wave of the pandemic.
For example, if the unequal drop in income caused a reduction in investment in education and training of the poorest members of the population, the effects of Covid-19 could have long-lasting and dire consequences for disadvantaged individuals entering the labour market in the future.
Where can I find out more?
- Covid-19-induced shocks and uncertainty: Article in the European Economic Review by Mirela Miescu and Raffaele Rossi.
- Inequalities in the times of a pandemic: Economic Policy article by Stefanie Stantcheva.
- Track the Recovery: Data on the economic impact of Covid-19 on people, businesses and communities across the United States.
- Economic policy uncertainty index: monthly data for the United States.
Who are experts on this question?
- Nicholas Bloom
- Yuriy Gorodnichenko
- Rachel Griffith
- Stefanie Stantcheva