The Poverty Eradication Coordination Unit (PECU) of the Office of the President together with the Department of Community Development of the Ministry of Local Government and Rural Development met with key stakeholders in Gumare and Maun 8th and 10th June to share the results of the recent poverty profiling exercise in the sub-district. The presentation and discussion of the results of the profiling exercise will inform the the completion of the profiling report, which will be the first of its kind in Botswana. The key stakeholders were drawn from government, private sector, non-governmental and civil society organisations.
In his welcome remarks and stating of the objectives of the meetings, the National Coordinator of the Poverty Eradication Programme Mr. Montshiwa Montshiwa said that the profiling of poverty in the Okavango sub-district is the first in a series of districts and sub-districts to be covered in the months to come. He commended the participants for their contributions to the profiling exercise, which he said went smoothly despite the challenges of the tough terrain of the sub-district and limited resources. He said that as the first sub-district to be profiled, their lessons will be used in other districts as the profiling exercise is rolled out countrywide. Okavango was chosen as the first sub-district in the exercise due to the high levels of poverty and need for urgent and comprehensive attention as noted by His Excellency the President of Botswana.
The profiling of the Okavango sub-district and the ones that will follow adopted the multi-dimensional approach to measuring poverty as opposed to the monetary based approach that is commonly used in national statistics. This is borne out of Botswana’s recent decision to adopt a multi-dimensional approach to poverty. The multidimensional poverty index (MPI) is an international measure of acute multidimensional poverty covering over 100 countries across the globe, capturing not only monetary poverty measures, but deprivations in health, education and living standards that a person faces simultaneously. Since 2019, UNDP Botswana has collaborated with the Oxford Poverty and Human Development Initiative (OPHI) to provide technical support throughout the steps to ensure the effective realisation of the adoption of the global multidimensional approach to poverty. In 2020, Botswana was included in the global MPI measure for the first time.
Alongside the global measure, Botswana has developed a national Multidimensional Poverty Index (MPI), which is the basis on which the profiling of poverty was done. The policy shift from the monetary based approach to poverty was borne out of the desire to be comprehensive and targeted as well as leave no one behind in addressing poverty in all its dimensions and manifestations. The MPI provides the means to understand poverty in all the dimensions that define one’s life, enabling policy makers to allocate resources and design policies and programmes more effectively.
The key findings from the profiling exercise show that the Okavango sub-district is disproportionately poverty-stricken, with monetary poverty level of 37.7% and multidimensional poverty level of 34.6% against the national levels of 16.3% and 17.2% respectively. At 68%, the sub-district has a significantly high number of households that are headed by females. The unemployment level is also very high, with 8,142 households heads unemployed out of a total of 10,373 captured in the sub-district’s data system. Further, the level of education attainment is extremely low with only 10.5% of the households heads having attained at least a General Certificate of Secondary Education (BGCSE). Access to sanitation services and the level of use of electricity were also very low, with 66% of the households having no toilet facilities and only 27% of the households using electricity as a source of lighting. On average, the households own very few assets, hence, coupled with the high level of unemployment, the sub-district’s sources of livelihood are highly limited. For instance, the average number of domestic animals owned by households are 8 for cattle and goats, 4 for donkeys and pigs, 10 for chickens and 2 for horses. These figures of ownership of domestic animals are far below the thresholds for a household to be considered not poor.
The profiling has identified prominent types of poverty in the sub-district, being, societal, income, shelter and sanitation, and food poverty. The key poverty drivers have been found to be lack of employment opportunities; non-availability of basic infrastructure and limited market access which make it challenging for households to pursue profitable economic activities; uncoordinated policies and programmes and their ineffective targeting; as well as human/wildlife conflicts given that the sub-district is in the geographical area where there are large numbers of wildlife species. These very specific findings provide the opportunity to formulate relevant policy responses to address poverty in the sub-district, which underscores the usefulness of the multidimensional approach to measuring and understanding poverty.
Beyond the profiling exercise, the profiling report recommends targeted and sustainable policy and programme interventions to address the factors that drive poverty in the sub-district. For example, the report recommends policy interventions that, alongside the improvement of the physical infrastructure should be geared towards improving the level of education, which in the medium to long term should be expected to improve the level of uptake of profitable economic opportunities, including the poverty eradication and economic empowerment programmes and projects that are rolled out by different government departments. The recommendation to improve the employment opportunities proposes the optimisation of sustainable natural resource management that are in the sub-district such as tourism-oriented income generating activities and the development of the value chains within the tourism and natural resource sectors.
Indeed, the meetings provided a great opportunity to bring together the key stakeholders to discuss the poverty issues in the sub-district. The stakeholders reflected on the necessity to adopt coordinated approaches and partnerships in policy formulation and implementation of interventions to address poverty. The government departments and community leadership highlighted the need to work closely together in policy and programme formulation and implementation to ensure optimal use of the scarce public resources that are at their exposal.
The private sector, NGOs and CBOs representing different sectors ranging from women and youth empowerment, education, natural resources conservation, and fight against gender-based violence, among others. They were very appreciative of the poverty profiling report and its recommendations. They expressed that the findings of the report will assist them tremendously in the development of their strategies and programmes to effectively support the communities to address poverty. There was particular emphasis on the importance of partnerships between these entities and the government and the communities to enable targeted and effective response to poverty in the sub-district.
Overall, the profiling report and its presentation brought about useful lessons about the implementation of the national MPI. These lessons will be of great value as the government embarks on rolling out the other pilot profiling exercises in other districts and sub-districts. For UNDP, the experiences and lessons are extremely informative to the design of programmes in other areas of the country across an array of issues, including for environment and climate change and women and youth empowerment. As UNDP continues its support to the government in the roll-out of the national MPI, it will important to bring the lessons learned from Botswana to the global Multidimensional Poverty Peer Network (MPPN) to continuously improve the approach and ways in which governments can bring these statistics to life as they work to improve the lives of their citizens.
