The Kovid-19 epidemic was accompanied by disruption of supply chains, rising commodity prices and inflation, rising public and private debt, and declining economic output. Despite the secular trend towards its eradication, income poverty (see here and here) has increased in 2020 due to the transient situation. Our recent research highlights the growth of “Extreme poverty115 million people in 2021 due to the Covid-19 effect (Figure 1). Using other poverty lines and expanding the forecast horizons from 2021 to 2030, we notice a dramatic increase in the major numbers of poverty in our COVID-19 counterfactual calculations. The results of the extreme poverty discussed here and here seem to agree on the direction and extent of Covid’s influence. At HeadCount Level-19 by 2021.
Figure 1. Number of poverty according to the poverty line
Source: Author details.
Note: SPL stands for Social Poverty Line, which represents the daily average level of per capita income or expenditure in the household survey. SPL contains both absolute and relative characteristics of poverty. Obtained global aggregated poverty headcount statistics from 5,000 country-specific annual random simulations from 2021 to 2040. Estimates are based on the constant 2011 PPP. Uses 2000-2020 data collected before baseline lockdown begins. Covid-19 Counterfactual 2020 updates the growth rate data that is realized or predicted in four variables made in 2021: country-specific average income, global income, country-specific absolute inequality, and global commodity prices.
Outside the number of poverty: macro-poverty vulnerability
COVID-19 had another effect on poverty. Amid epidemics and uncertainty about the future of the global economy, COVID-19 has increased the number of people at risk of falling into poverty. We have simulated the evolution of poverty in developing countries, considering the uncertainty surrounding country-specific factors such as global economic growth and commodity prices and income distribution. Figure 2 shows the uncertainty embedded around global extreme poverty across the time horizon.
Figure 2. Global Extreme Poverty and the COVID-19 Crisis
Source: Author’s details.
Note: The results are based on the US $ 1.90 a day poverty line in the constant 2011 PPP. Global aggregate poverty statistics have been obtained from 5,000 country-specific random simulations from 2021 to 2040. Panel A: Between 2021 and 2030, the expected poverty numbers will be 8.3 percent and 5.9 percent, with a deviation of 0.263 percent. , Respectively. Panel B: By 2021 and 2030, the expected poverty rate will be 9.8 percent and 7.3 percent, respectively, the standard deviation of 0.32 percent and 0.73 percent.
We then define the poverty-protected population as those with an average of 99.5 percent of the simulated poverty headcount trajectory. The COVID-19 epidemic increased the poverty-protected population across all the studied poverty lines (Figure 3). To distinguish it from other measures of poverty weakness, we call our measurement “macro-poverty weakness”: Dang and Lanjouw (2017) and Lopez-Calva and Ortiz-Juarez (2014).
Figure 3. Poverty vulnerability by poverty line
Source: Author’s details.
Note: SPL stands for Social Poverty Line. Baseline and COVID-19 estimates use the IMF GDP per capita growth rate reported in October 2019 and April 2021. Results are obtained from 5,000 country-specific random draws each year.
Effects of COVID-19 on Poverty Weakness
The COVID-19 shock has permanently increased the risk of poverty due to considerable uncertainty about the future global prospects. The short- and long-term effects of the epidemic measured by a COVID-19 counterfactual indicate an increase in the number of people at risk of becoming 40 and 107 million people using the 90 1.90 poverty line between 2021 and 2030 (Figure 3).
Poverty Weakness and concussion of heads
How does macro-poverty vulnerability change with the poverty line? We find a concave connection between the number of poverty and the weakness of poverty (Figure 4). This concavity is pushed upwards and to the right after the epidemic, indicating that society faces more poverty and is at greater risk of falling into poverty after COVID-19. Maximum Aggregate-Poverty Weakness: The highest number of people in the global income distribution is potentially becoming poorer, catching around the US $ 5.5 line in both 2021 and 2030. 330 million, with a poverty line of US $ 3.20 to US $ 5.50.
Figure 4. Poverty vulnerabilities and major numbers worldwide
Source: Author’s details.
Note: Baseline and COVID-19 estimates use the IMF GDP per capita growth rate reported in October 2019 and April 2021. Results are obtained from 5,000 country-specific random draws each year The reported poverty headcount numbers are moderate estimates.
Regional Extreme Poverty Weakness
Since the onset of the epidemic, developing regions have increased the risk of extreme poverty across the horizon (Figure 5). In 2021, South Asia (SAS) and sub-Saharan Africa (SSA) were the most at-risk population regions. By 2030, both Baseline and Covid-19 counterfactuals show that East Asia and the Pacific (EAP) and the SSA region will have the most poverty-stricken people: approximately 230 and 290 million people, respectively. The simulations indicate that Latin America and the Caribbean (LAC) and South Asia will experience the most significant growth of the poverty-stricken population between SAS 2030: 20 and 55 million.
Figure 5. Regional poverty vulnerabilities
Source: Author’s details.
Note: The results are based on the US $ 1.90 a day poverty line in the constant 2011 PPP. HIC means high income country. Developing regional names: ECA stands for Europe and Central Asia, MNA stands for Middle East and North Africa, SAS stands for South Asia, LAC stands for Latin America and the Caribbean, EAP stands for East Asia and the Pacific, and SSA stands for Sub-Saharan Africa. .
The increase in the number of people at risk of extreme poverty is particularly relevant in LAC. By 2030, the LAC population will be at risk of poverty which will be the highest among all regions. It will go from 22 in the baseline to 25 per cent in the Covid-19 counterfactual. Similarly, the share of the poverty-stricken population in the SSA will be higher: by 2030, the baseline of Covid-19 and in both subsequent cases will be 21 percent.
Conclusion
Increasing poverty indicates the need to establish or strengthen preventive measures against global and diverse shocks that affect country-specific and regional development. Security nets, relocations, and other poverty alleviation programs should be planned and monitored, including delays for those who fall into poverty. Measurement of vulnerabilities such as those described here should play an important role in identifying the negative risks that affect poverty alleviation.