One in five households is ‘multidimensionally’ poor

While the leading indicator of poverty is monetary income, global experts are increasingly studying the different dimensions of hardship to better guide policies and interventions.

Ten years after the University of Oxford and the United Nations launched the first study into multidimensional poverty, Statistics Botswana last week released its own research using the Botswana Multi Topic Household Survey (BMTHS) of 2015-2016 as a basis. The BMTHS is the most recent multi-topic dataset showing detailed household economic activity for the country across indicators such as education, employment, well-being, healthcare and others.

“Botswana has been using the two uni-dimensional monetary poverty measures of extreme poverty and national Poverty Datum Line to track progress in the fight against poverty,” the pilot study’s researchers state.

“Monetary measures, however, do not capture the multiple and overlapping non-income deprivations experienced by the poor such as education, health, housing, sanitation and access to clean drinking water.”

Statistics Botswana researchers say government has long acknowledged that poverty has many faces as seen in programmes such as the food basket for destitute persons, feeding programmes for orphans and the vulnerable, poverty eradication schemes, Youth Development Fund and others.

Still, the results of the first study into multidimensional poverty in the country are depressing. Where the UN’s Global Multidimensional Poverty Index (MPI) report for 2020 estimates that 17.2% of Batswana are multidimensionally poor with 3.5 percent classified as extreme, Statistics Botswana’s own pilot study has found that 20.9% of Batswana are multidimensionally poor with 3.9 percent classified as extreme.

At the national level, the most pressing dimensions of poverty outside of incomes are lack of access to ICT or computer use, sanitation, food security and assets.

According to the methodology adopted by Statistics Botswana, a household is considered deprived of computer use if no member has used a computer in the last 12 months. Deprivation in sanitation is when a household has no toilet facilities or open-pit latrine. A household is deprived in food security if it reports experiencing any moderate or severe food insecurity. Deprivation in assets is if a household does not own at least three of the following assets: four cattle, 12 small stock, 25 chickens, a car, a tractor, a truck or donkey, a cart, a fridge and a phone.

“(The study also shows that) 15.9% of the population, though not multidimensionally poor, are vulnerable to poverty, and therefore should also be assisted accordingly to build resilience to shocks such as drought,” the researchers say. In as much as it has many faces, poverty is also not uniformly distributed in the country. The study confirms previous research showing that poverty is worse in rural areas than in urban villages, cities and towns.

“Rural areas suffer higher poverty compared to cities and towns, and this could be an indication of the inadequacy of some of the basic infrastructure such as water reticulation and electricity in rural areas.

“In fact, rural areas are the only ones with a multidimensional poverty index that is higher than the national average.

“On the other hand, cities and towns have lower poverty incidences, indicating the availability of most basic services in these areas.”

The researchers add: “Those who experience severe multidimensional deprivations are mostly found on the outskirts of urban villages as well as in remote rural areas where most basic services are not available.” As with previous poverty studies based on incomes, multidimensional poverty is also most concentrated in the Kweneng West and Ngamiland West, while the mining towns of Jwaneng and Orapa have the least challenges. Only Ngamiland West and Kweneng West have more than 10% of their respective populations living in severe multidimensional poverty.

Kweneng West and Central Bobonong also have the highest populations of people vulnerable to poverty, meaning they are least prepared for shocks such as drought and other natural disasters. “In general, towns and cities have lower MPIs, closer to zero, compared to remote areas indicating that the deprivation levels are higher in remote areas than in towns.”

Researchers say while the pilot study into multidimensional poverty has its limits, such as being based on the older 2015-2016 BMTHS whose interviews were not necessarily finetuned to measuring MPI, it is important in detailing the exact deprivations experienced by the poor as well as the drivers of poverty.

The researchers are also recommending that while awaiting a final national MPI, the pilot national MPI, together with monetary measures, should be used for planning and allocation of resources in the country.

“This could be piloted in areas with the highest incidence of poverty as well as those with high numbers of poor people.

“There is the need to address nutrition, food security, computer skills and access to sanitation amongst the poor.

“Addressing these deprivations will not only make an impact on the MPI, but will also contribute to a further reduction in health-related aspects of poverty such as malnutrition and child mortality.

“Increasing agricultural production will also go a long way in addressing food insecurity amongst the poor.”