The World Bank now forecasts an that COVID-19 will push 88 million to 115 million people into poverty in 2020. Extreme poverty in this case is defined as living on $1.90 or less per day. This is the first reversal in global poverty in decades taking us back 3 years. The change in trend is very sharp, see figure on page 5.
Many of the new poor are in the urban informal sector, where government redistribution is unlikely to help. The world bank report stresses government interventions in poor countries, but the informal sector is hard to reach (unregistered, less politically powerful, less organized).
Some of these mechanisms are intensified by lockdown policies. The World Bank’s report scrupulously avoid that connection, but I suspect it is important. Disambiguating between rich-country lockdowns and poor country lockdowns is important.
Rich county lockdowns
Much of the effect comes from the contraction of global gdp of 5-8 percent. To the extent that lockdowns increase the GDP reduction, they contributed to the loss.
The decisions of the wealthiest countries to lockdown contracted demand for tourism and manufactured goods. South-Asian exporters like India, Bangladesh and Indonesia come up repeatedly in the report. Also the new poor are more urban and formerly worked in tourism and manufacturing. This suggests that western consumer choices contributed to the increase. Probably a minority of total change, roughly.
Poor Country Lockdowns
Like in west, service workers have the least education. They got hit the hardest by lockdowns in counries like India and Ethiopia.
Millions of Indian migrant workers had to migrate by foot in one crazy week in India. Documented events along indicate hundreds of deaths. Malnutrition likely the biggest killer. Kids have a lot if QALY’s left.
Total effect?
Back of the envelope calculation. Let’s assume the increase in poverty is 110 Million. It’s unclear when he affect washes out over time, but let’s say that it persists for 5 years. Currently 40% of the extreme poor in SSA and south Asia are 0-14. Over five years, the number of children who will go through the dangerous begining of life will be
110 x 10^6 x .4 x .33 = 15 x 10^6 additional children growing from 0 to 5 in extreme poverty.
A cursory look at OWID’s child mortality and income plots suggests the change in child mortality is about 5%. So assume that an 5% additional counterfactual deaths. Assume 70 QALY’s per child.
5 x 10^6 x .05 x 70 = 54 * 10^6 lost QALYs
Then also assume that lockdowns caused 1⁄4 of the increase in global poverty. Just a guess.
54 x 10^5 / 4 = 13 x 10^6 lost QALYs from lockdowns.
Given my high uncertainties, 1.3 to 130 QALY’s is a 95% range.
This only includes from those people that crossed the magic line at $1.9 / day. Non-extreme poverty also increased.
Building on your statement that many of the affected will be hard to reach with aid payments: some study on just what amount of government redistribution is actually helpful might also be in order. Redistribution may solve the immediately obvious problems of people being suddenly unemployed, but it also slows the economy’s ability to adapt to the significantly changed environment. So there’s undoubtedly a crossover point where it hurts more than it helps in the long run.
Not that I expect most governments would pay any attention at all if somebody did work up a number or a formula, but being able to see which nations come closest to hitting it could be entertaining.
The World Bank now forecasts an that COVID-19 will push 88 million to 115 million people into poverty in 2020. Extreme poverty in this case is defined as living on $1.90 or less per day. This is the first reversal in global poverty in decades taking us back 3 years. The change in trend is very sharp, see figure on page 5.
Many of the new poor are in the urban informal sector, where government redistribution is unlikely to help. The world bank report stresses government interventions in poor countries, but the informal sector is hard to reach (unregistered, less politically powerful, less organized).
Some of these mechanisms are intensified by lockdown policies. The World Bank’s report scrupulously avoid that connection, but I suspect it is important. Disambiguating between rich-country lockdowns and poor country lockdowns is important.
Rich county lockdowns
Much of the effect comes from the contraction of global gdp of 5-8 percent. To the extent that lockdowns increase the GDP reduction, they contributed to the loss. The decisions of the wealthiest countries to lockdown contracted demand for tourism and manufactured goods. South-Asian exporters like India, Bangladesh and Indonesia come up repeatedly in the report. Also the new poor are more urban and formerly worked in tourism and manufacturing. This suggests that western consumer choices contributed to the increase. Probably a minority of total change, roughly.
Poor Country Lockdowns
Like in west, service workers have the least education. They got hit the hardest by lockdowns in counries like India and Ethiopia. Millions of Indian migrant workers had to migrate by foot in one crazy week in India. Documented events along indicate hundreds of deaths. Malnutrition likely the biggest killer. Kids have a lot if QALY’s left.
Total effect?
Back of the envelope calculation. Let’s assume the increase in poverty is 110 Million. It’s unclear when he affect washes out over time, but let’s say that it persists for 5 years. Currently 40% of the extreme poor in SSA and south Asia are 0-14. Over five years, the number of children who will go through the dangerous begining of life will be
110 x 10^6 x .4 x .33 = 15 x 10^6 additional children growing from 0 to 5 in extreme poverty.
A cursory look at OWID’s child mortality and income plots suggests the change in child mortality is about 5%. So assume that an 5% additional counterfactual deaths. Assume 70 QALY’s per child.
5 x 10^6 x .05 x 70 = 54 * 10^6 lost QALYs
Then also assume that lockdowns caused 1⁄4 of the increase in global poverty. Just a guess.
54 x 10^5 / 4 = 13 x 10^6 lost QALYs from lockdowns.
Given my high uncertainties, 1.3 to 130 QALY’s is a 95% range.
This only includes from those people that crossed the magic line at $1.9 / day. Non-extreme poverty also increased.
Building on your statement that many of the affected will be hard to reach with aid payments: some study on just what amount of government redistribution is actually helpful might also be in order. Redistribution may solve the immediately obvious problems of people being suddenly unemployed, but it also slows the economy’s ability to adapt to the significantly changed environment. So there’s undoubtedly a crossover point where it hurts more than it helps in the long run.
Not that I expect most governments would pay any attention at all if somebody did work up a number or a formula, but being able to see which nations come closest to hitting it could be entertaining.