One third of the way into our SDG journey, the world is not on track to achieve the global Goals by 2030. The coronavirus pandemic disrupted implementation towards many of the SDGs and, in some cases, turned back decades of progress. The first goal for the Sustainable Development Goals (SDGs) is to end poverty in all its forms everywhere. However, according to some worrisome simulation by the World Bank, the coronavirus fueled recession will push 100 million people into extreme poverty.
In an effort to fight to end poverty during these difficult times, the UNDP and the Oxford Poverty and Human Development Initiative (OPHI) released the Global Multidimensional Poverty Index (MPI) 2020 late last week. Although previously defined only in monetary terms, poverty is now understood to include the lived reality of people’s experiences and the multiple deprivations they potentially face. The global MPI examines each person’s deprivations across 10 indicators in three equally weighted dimensions—health, education and standard of living. It offers a high-resolution lens to identify two things; who is poor and how poor are they.
We have significant challenges associated with looming uncertainty; however, governments can make use of the multidimensional approach for crafting responses to the COVID-19 pandemic. Following are some major takeaways from the report in the context of Pakistan.
For starters, sixty-five countries, home to 96 percent of the population of the 75 countries studied, significantly reduced multidimensional poverty. In Pakistan, the multidimensional poverty fell from 44.5% in 2013 to 38.3% in 2018. 4 million people moved out of poverty over five years compared to 273 million people in India over 10 years, 70 million people in China over 4 years and 19 million people in Bangladesh in five years or so.
Trends in multidimensional poverty complement trends in monetary ($1.90 a day) poverty. In 52 of the 71 countries with both multidimensional and monetary poverty data, the incidence of multidimensional poverty fell faster in absolute terms, while the incidence of monetary poverty fell faster in 19 countries. In Pakistan, trends in the incidence of multidimensional poverty according to national definitions and the global MPI suggest that multidimensional poverty fell more slowly than monetary poverty. This hints at underlying structural issues such as jobless growth, rising inflation and deepening inequality.
As the poorest regions in the time periods studied, South Asia and Sub-Saharan Africa had the largest annualized absolute reductions in multidimensional poverty. The estimates of changes in multidimensional poverty over time can be used to project whether countries are on track to achieve the SDG target of at least halving the proportion of people living in poverty in all its dimensions by 2030 as well as the possible impacts of COVID-19. Before the COVID-19 pandemic, 47 countries were on track to halve multidimensional poverty by 2030, and 18 were off track if the observed trends continued – Pakistan will be in the latter category.
Of the 1.3 billion multidimensionally poor people, 82.3 percent are deprived in at least five indicators simultaneously. In Pakistan, 21.5 % of the population is in severe multidimensional poverty —that is, those with a deprivation score of 50 percent or more. 12.9% of the population is at risk of suffering multiple deprivations—that is, those with a deprivation score of 20–33 percent. 24.3% population is living below the national poverty line, while 3.9% of the population is living below the international poverty line of $1.90 (in purchasing power parity [PPP] terms) a day. In terms of contribution of deprivation in dimension to overall multidimensional poverty, 27.6% attributes to health, 41.3% to education and 31.1% to standard of living.
Two indicators under the dimension of health are nutrition and child mortality with 27% and 5.9% of the population deprived in each respectively. Years of schooling and School attendance are under the dimension of education with 24.8% and 24.3% of the population deprived in each respectively. Under the dimension of living standards, there are six indicators with the percentage of population deprived as follows; electricity (38.2), drinking water (29.4), sanitation (9.1), flooring (6.3), cooking fuel (35.9) and asset ownership (7.3).
In a country where size of the informal economy is generally quoted at 35% or one-third of the country’s GDP and 67% of urban employment is in the informal sector, there is a pressing need to target those who need it most in the midst of the pandemic.
The SDG Tech Lab established at Information Technology University in collaboration with UNDP and UNFPA has detected formal and informal slums through remote-sensing using Convolutional Neural Networks (CNN) and has assessed the socio-economic conditions of slum areas through a Multidimensional Poverty Index (MPI) framework in Lahore, Hyderabad and Peshawar. Based on detailed primary data collected and assessed by the Lab, the findings of the report are not surprising.
Here is the golden opportunity. It is imperative to harness locally identified solutions, such as that presented by the SDGTL. We are now in a position to not only identify where the highest deprivation is in major cities, we also know the depth of the deprivation. This creates the space to do efficient fiscal policy. This is the type of evidence you need to do evidence based policy. As an example, we can tell you that the next public primary school needs to be located near Muhamad Pura, the next basic health unit needs to be constructed near Tibba Kaccha. There is more where this comes from.
So the ball is the government’s court. In order to put the country back on track to achieve the Goals, make cities more inclusive and fulfill obligations to those who voted, now is an excellent opportunity to use smart policy and take a contemporary lens to the issue of poverty.
Overall, we must hold firm in our convictions and not let the crisis derail our hopes and ambitions. The continued pursuit of the Sustainable Development Goals is consistent policy. Consistency is a virtue.