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Politics & Economic Development in Africa

Faculty: John Doces (Political Science)
Student: Erik Heinemann (Political Science, ’15), Chanda Singoyi (Civil & Environmental Engineering, ’18)
DP&S Liaison: Janine Glathar, Luyang Ren
Date: Summer 2014-Present

Summary of ‘Authoritarian Rule & Poverty in Uganda’ – Summer 2014: Undergraduate student Erik Heinemann (Political Science, ’15) worked with Prof. John Doces (Political Science) and GIS Specialist Janine Glathar in the summer of 2014 to create a dataset (tabular & spatial) with subnational data for Uganda for variables such as poverty, access to clean water, access to latrines, and other indicators of development. Once the dataset was created, we created map layers to visualize Uganda’s subcounties by the markers of development – and we plotted the location of President Yoweri Museveni’s birthplace and the capital city (Entebbe). The goal was to create a distance co-efficient that could be used in a regression analysis to examine the extent to which peoples’ proximity to Museveni’s strongholds impacted their living conditions. Prof. Doces’ synopsis of the results is shown below, along with a link to a storymap that provides more information on the project:

In Africa, a common theme in development is that authoritarianism has been detrimental to development. In particular, arguments about the nature of this relationship focus on the role of the African “Big Man” and the effect of patronage politics viewing the situation as one in which people connected to the ruler benefit most from his rule. Most considerations of this idea, however, focus on country-level indicators, but this does not precisely test the underlying argument because the expected level of variation in development outcomes is within the country not necessarily across countries. To test this argument we thus focus within Uganda and how “Big Man” rule has affected development there. We do this using a sub-county spatial analysis of Uganda employing GIS mapping techniques and a regression analysis to test if there is an effect of “Big Man” rule and sub-county development. To measure the influence of the Big Man, here Yoweri Museveni, we calculate each sub-county’s distance to his birthplace as well as distance to Entebbe, Uganda’s capital city. We expect both to be inversely associated with development at the sub-county level. To measure development we use indicators of sanitation including the percentage of households with access to a latrine and access to soap for hand-washing. Our spatial maps show a clear association between distance and development indicating that the further a sub-county is from where Museveni was both there are lower levels of development. Moreover, our regression analysis shows that controlling for a number of other variables—e.g., poverty rate, poverty density, population density, urban sub-county, and total households—that the effect of distance from both Museveni’s hometown and distance from Entebbe both are statistically significant and inversely associated with our development indicators. Specifically, a one standard deviation increase in distance from Museveni’s hometown is associated with a fall in latrine coverage by half of a standard deviation or about 32% less coverage. Alone the two measures of distance explain roughly 45% of the variation in development outcomes and the full models explain almost 60% of the variation.

Showcase story map for Authoritarian Rule & Poverty in Uganda

Summary of Politics & Economic Development in Africa – Spring/Summer 2017: Undergraduate student Chanda Singoyi (Civil & Environmental Engineering, ’18) picked up work on Prof. Doces’ research after Erik Heinemann (Political Science, ’15) graduated. Starting in spring 2017, Chanda worked with GIS Web Application Specialist Luyang Ren and Prof. Doces on using satellite data on nighttime lights as a means of measuring economic development at the subcounty level in Uganda. He has hopes of expanding this analysis to other countries in sub-Saharan Africa. As with the first round of this project, a regression analysis will be performed to assess the relationship between proximity to President Museveni’s strongholds and a subcounty’s level of development.

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