The Covid-19 has had a huge negative impact on lives and livelihoods, disproportionately affecting the poor and vulnerable. To shed light on the possible healing effects, this column studies the effect of five past pandemics on production, unemployment, poverty and inequalities in the short and medium term. The results show significant negative effects, although countries that provided relatively large budget support experienced limited production declines. Historically, increases in unemployment, poverty and inequality have been smaller in countries with greater budget support and relatively stricter initial conditions, including higher formalities, family benefits and health spending.

The Covid-19 has had a huge negative impact on lives and livelihoods, disproportionately affecting the poor and vulnerable. The IMF (2021) warns that while global growth is expected to recover, divergent recoveries are occurring between and within countries, with a high risk of lingering economic damage for many. Recent research suggests that past pandemics have increased income inequality and hurt the employment prospects of those with low education (Furceri et al. 2020). Those effects could be stronger this time around, given the considerably wider reach of Covid-19.

Could policies help? Furceri et al. (2021) show that fiscal policy has played an important role in reducing or amplifying income inequalities in past pandemics. Ma et al. (2020) find that the negative effects on GDP and unemployment were smaller in countries with larger first year responses in public spending, especially in health care. We continue this discussion in our recent work (Cuesta Aguirre and Hannan 2021).

Past pandemics have had adverse macroeconomic and distributional effects

Based on a sample of 55 countries over the period 1990-2019, we estimate the impact of five recent modern pandemics (SARS in 2003, H1N1 in 2009, MERS in 2012, Ebola in 2014 and Zika in 2016) on the main economic indicators. We use local projections to estimate the dynamic impulse response functions of pandemic events (dummy variable representing the pandemic year) on our variables of interest. The regressions include time and country fixed effects and relevant control variables (see note to Figure 1).

The results confirm that pandemics have lasting negative effects on the economy (Figure 1). Production declines 2.2% three years after a pandemic and does not return to pre-pandemic levels within five years, underscoring that the scarring effects of pandemics tend to persist. Likewise, the unemployment rate – which tends to increase by one percentage point after four years – remains above pre-pandemic levels after five years. Pandemics are also associated with a 1.1 percentage point increase in the poverty rate one year later, and this effect persists after five years. The poverty gap – a measure of the intensity of poverty (average lack of income or consumption relative to the indicated poverty line) – also increases following a pandemic and persists over the medium term (suggesting that pandemics not only increase the share of the population living in poverty, but also intensify the hardships of those living in poverty). Finally, inequality, measured by the net Gini index, increases by 1.7% after five years.

Figure 1 The effect of past pandemics

To note: The impulse response functions of the relevant variable on pandemics are estimated using a sample of 55 countries over the period 1990-2019. The solid line indicates the answer while the dotted lines correspond to 90% confidence bands using standard errors grouped at the country level. The x-axis represents time: t = 0 is the year of the change. The y axis represents the change in the variable of interest at time t, compared to the year preceding the pandemic. Poverty refers to the WDI poverty rate of $ 1.90 per day (2011 PPP; as a percentage of population), while inequality is represented by the net Gini index from the SWIID database. All equations include one dummy variable (and two lags) to capture the pandemic, two lags of the dependent variable, two lags in production, and country and time fixed effects. In addition, the output and unemployment rate equations control for two lags: log per capita income, trade-to-GDP ratio, private credit-to-GDP ratio, and banking crisis.

Strong policies and structural features help

So, how do you mitigate these scar effects? We study the role of fiscal policy (using the fiscal impulse – the negative of the change in the structural primary balance) and the initial conditions of informality (economic activities hidden from official authorities), family benefits (expenditure component social services; public expenditure on family benefits, including financial assistance reserved exclusively for families and children) and health expenditure per capita. For each political / structural characteristic studied, the baseline regressions were augmented by interacting the pandemic shock with “high” and “low” dummy variables, where high and low represent countries above or below / equal to the median the respective political / structural characteristic across the sample during the pandemic year (fiscal policy), the year preceding the pandemic (informality and health), or using the decade average (family benefits).

The results suggest that countries that provided relatively higher budget support had comparatively better production results, with production falling 1.5% after three years, compared to 3.4% for those with relatively higher budget support. low (Chart 2). We also find that countries with higher budget support and better initial conditions performed relatively better in terms of unemployment, poverty and inequality. For example, the poverty rate increases by 1.3 percentage points after the first year for countries with relatively higher informality, compared to an increase of 0.7 percentage point over the same period for those where informality is lower. Five years after the pandemic, the poverty rate remains one percentage point higher than pre-pandemic levels for countries with higher informality, compared to an increase of 0.4 percentage point for those where l informality is lower. Similarly, the increase in inequalities is 2.2% after five years for countries with lower family allowances, against 1.5% over the same period for those with higher family allowances. Finally, inequality increases to 1.2% after five years for countries with relatively lower health expenditure per capita, compared with a 0.6% increase for the high expenditure group over the same period. These results are robust to a battery of alternative specifications (discussed in our article).

Figure 2 Differential responses three years after a pandemic shock

To note: The bars show the coefficient of the impulse functions three years after the pandemic shock: the estimated change in the variable of interest three years after the pandemic shock, compared to the year before the pandemic. Solid bars represent statistically significant variables (90%) for at least one year of time horizons t = 0 to t = 5.

Several channels are at play. For example, fiscal measures provide resources to vulnerable segments of the population, such as those at risk of poverty and those disproportionately affected by the challenges of the pandemic (for example, a relatively reduced access to quality health care, job loss in contact-intensive industries, and personal savings to support livelihoods in the event of job loss). The World Bank (2021) documents in detail the channels through which informality worsens the effects of Covid-19 – informal sector workers tend to be less skilled and less well paid, with limited access to social safety nets and finance, while informal businesses tend to have labor-intensive production and are more prevalent in the service sector (which is more likely to be affected given the contagious factor related to Covid-19).

This time around, policies are even more crucial

Some Covid-specific effects indicate greater adverse effects for countries with weaker initial conditions. For example, social distancing during the pandemic has meant the use of online education in many countries. To the extent that countries with higher informality are characterized by lower Internet access, already comparatively lower enrollment rates could be exacerbated, leading to a persistent loss of human capital and a deterioration in poverty outcomes. and inequality (Figure 3). Higher informal economies also tend to have a lower proportion of the population with a checking account at a financial institution or with a mobile money service provider (which would affect access to financial resources). Likewise, countries with lower social spending have less access to the Internet and financial services, which could exacerbate poverty and inequality outcomes. These characteristics further underline the need for supportive political actions. Adequate budget support, higher health spending and targeted family benefits should be part of the package. Greater political support and complementary policies may be needed in countries where informality is high and which may – as our results suggest – witness more negative impacts on unemployment, poverty and poverty. inequality.

figure 3 Informal indicators versus development indicators

Source: WDI and Medina and Schneider (2020).

Authors’ Note: The views expressed herein are those of the authors and should not be attributed to the IMF, its Executive Board, or its management.

The references

Cuesta Aguirre, JP and SA Hannan (2021), “Recovery After Pandemics: The Role of Policies and Structural Features”, IMF Working Paper Series WP / 21/181.

Furceri, D, P Loungani, JD Ostry and P Pizzuto (2021), “Fiscal austerity intensifies the increase in inequalities after pandemics”, VoxEU.org, 03 June.

Furceri, Da, P Loungani, JD Ostry and P Pizzuto (2020), “Covid-19 will increase inequalities if past pandemics are a guide”, VoxEU.org, May 08.

IMF (2021), “Managing Divergent Collections”, Global economic outlook, April.

Ma, C, J Rogers, and S Zhou (2020), “Modern Pandemics: Recession and Recovery,” International Finance Discussion Papers 1295. Washington: Board of Governors of the Federal Reserve System.

Medina, L and F Schneider (2020), “Shedding light on the shadow economy”, Mondial economy 21 (2): 25-82.

World Bank (2021), The long shadow of informality, challenges and policies, F Ohnsorge and S Yu (eds), Washington DC.