Multidimensional poverty in Senegal : a non-monetary approach using basic needs By Jean Bosco KI Sixth PEP General Meeting Lima, Peru 1
Presentation plan 1. Objectives and methodology 2. Results 3. Conclusion 2
Objectives and methodology The main objective of this research is to construct a composite indicator of multidimensional poverty using basic needs. That will also make it possible to explore the link between monetary and non-monetary poverty. We use Multiple Correspondence Analysis (MCA) to construct the Composite Poverty Indicator (CPI). MCA is a method that enables data reduction while preserving essential information. 3
Objectives Methodology The dimensions used in the building of our composite indicator are related to education, health, drinking water, food, housing, energy, communication, housing equipments and comfort elements. For a given household, the value of the CPI is a linear combination of binary indicators describing its well-being with weights resulting from MCA as indicated by the following formula: 4
The first factorial axis that correspond to the horizontal axis, describes well-being; it opposes poor to non-poor. 5
Typology of poverty Households are not all affected by the same type of poverty. The forms of non-monetary poverty which are the most prevalent are related to vulnerability of human existence (low human capital, difficult living conditions), lack of infrastructures, and elements of comfort and housing. 6
RESULTS Relationship between Composite Poverty Indicator (CPI) and household characteristics Position of rural and urban areas on the CPI : the following graph indicates that rural area is located in the poverty zone whereas urban area is located in the non-poor zone. 7
RESULTS Relationship between CPI and sex of household chief: On this graph, male household heads are located on the poverty zone while female household heads are located on the non-poor side. 8
RESULTS Composite poverty indicator and household size This graph indicates that poverty increases with household size 9
RESULTS Composite Indicator and activities of the household head: The graph indicates that farmers are poorer than other people. 10
RESULTS Composite Indicator and marital status Polygamists are poorer than people of other marital status. 11
RESULTS Link between monetary and non monetary poverty The following graph indicates that a positive link exists between monetary and multidimensional poverty The correlation coefficient between the composite indicator and the per capita expenditure per equivalent adult is 0.47 and the correlation coefficient of the ranks is 0.60 12
RESULTS Incidence of multidimensional poverty We compute the CPI of a household just meeting basic needs. We interpret this value as a poverty line. In our case it is 0.088 All in all, the obtained results are similar to those of the monetary approach but with some divergences. The proportion of poor is 60% and the poorest groups are related to living in a rural area, being farmers, living in large families The following table indicates that for the two forms of poverty (monetary and non-monetary), rural area is affected more than the urban one. Population in the rural area are affected more by the multidimensional poverty, whereas those in the urban area are especially affected by monetary poverty Variables Urban area Rural area Total Multidimensional poverty Incidence (1) 22.3 92.3 60 Monetary poverty incidence (2) 37.6 64.9 48.5 Gaps (1)-(2) -15 27.4 11.5 13
RESULTS Prevalence of double poverty Double poverty is about households who are affected by the two forms of poverty, (monetary and non-monetary). The results of the study indicate that double poverty affects especially the poorest group (rural area, farmers, large family... ). The following table indicates that population in rural area are particularly affected by the two forms of poverty (59.6%) whereas population who are not poor according to the two concepts of poverty are located in the urban area (55.8%). The proportion of population who are poor according to multidimensional poverty but non-poor for the monetary poverty is particularly high in rural area (32.7%). The proportion of population who are non-poor according to multidimensional poverty but poor for the monetary poverty is particularly high in urban area (21.19%). Urban area is especially affected by monetary poverty despite of the existence of infrastructure, human capital and comfortable housing. These results suggest the imperfection of markets. Multidimensional and monetary poor Multidimensional poor and monetary non-poor Multidimension al non-poor and monetary poor Multidimensional and monetary non-poor Total Urban area 15.7 6.6 21.9 55.8 100 Rural area Total 59.6 40.8 32.7 19.2 5.3 7.7 2.4 32.3 100 14 100
Convergence and divergence of monetary and nonmonetary poverty by region 15
Conclusion From Multiple Correspondence Analysis, we constructed a composite indicator of multidimensional poverty. This composite indicator orders households according to their well-being. The results indicate the existence of three main forms of nonmonetary poverty: vulnerability of the human existence, poverty in infrastructure, and poverty in comfort. The poorest groups are related to the rural zone, farmers, large family... These same poorest groups are affected by double poverty (monetary and non-monetary). Those in the rural area are affected more by the multidimensional poverty, whereas those in the urban zone are especially affected by monetary poverty. Finally a clear positive link exists between multidimensional and monetary poverty. 16
Thank you for your attention 17