"Statistics a measure for Development"

• Home
• Executive Summary
• Abstract
• Introduction
• Data and methods ▼
• Spatial Patterns ▼
• Spatial Relationships ▼
• Conclusions
• Maps

Spatial Trends of Poverty and Inequality in Uganda: 2002-2005.

The Uganda Bureau of Statistics (UBOS) has put at the disposal of policy-makers and stakeholders down to the sub-county level a powerful tool to be used for informed decision-making. The tool is a poverty mapping and analysis publication, entitled “Spatial Trends of Poverty and Inequality in Uganda: 2002-2005”.

The publication, is a result of the collaborative effort of the Makerere University Faculty of Economics and Management, the Department for International Development (DFID) of the UK, the International Livestock Research Institute (ILRI), and the World Bank.

The results are based on the 2002 Uganda Population and Housing Census (UPHC) and the 2005/2006 Uganda National Household Survey (UNHS). They show a general improvement in the welfare of all Ugandans except in some parts of the north and north east. No attempt has been to analyse the deeper causes of the variations in regional trends other than a postulation that war in the north, as well as ecological and topographic factors, could account for the differences.

The publication outlines the Poverty Incidence (also called poverty head count) for each district and sub-county that existed before 2006. This is the proportion of the population that was living below the poverty line, calculated as shs23,150 for per month for Kampala and shs 20,308 for Kasese rural, at 1997 prices.

Other indicators measured include the Poverty Density ie the number of poor people per square kilometre in a sub-county. The Poverty Gap ie the difference between the average expenditure of a household and the poverty line, is also measured.  There is also the Gini-Coefficient which deals with poverty inequality within the sub-county. The Gini ration ranges from 0, where there is no difference between consumption expenditure among households in a sub-county and 1, where a single household is responsible for all the expenditure in the entire sub-county. Various shades and layers of colours have been used in the maps to illustrate the differences in poverty levels between one sub-county and another. It is hoped that the colour shades will instantly portray the intended effect to the reader.

New districts have been created since the 2002 UPHC and the 2005/006 UNHS. Their information can however be found under the county or counties in the old district from which the new district was curved.

These sub-counties results, when triangulated with educational and health data, indicate a close relationship between poverty and social service delivery. For instance where the poverty density was found to be very high the provision of educational facilities and health services was also found to be wanting.  

Kenya is among the developing countries that have used such results of poverty mapping to allocate resources to constituencies and to predict impacts of different policies. But this is the first time such a high resolution mapping, down to the sub-county level, is analysed for Uganda. It is on those grounds that I now invite the policy-makers and stakeholders to come and utilize the data to inform their decisions.

J. B. Male-Mukasa
Executive Director
Uganda Bureau of Statistics