Who Talks to the Chief, Who Builds the Party?

• In Event: African Legislatures and Horizontal Accountability

Abstract

The influence of chiefs and other intermediaries on party-politics is a widely discussed topic in the research on Africa. This argument is mostly framed in the logic of local patronage networks and these relations are often described as shortcuts to the population that enhance the strategic coordination between voters and candidates in countries with weakly institutionalized political parties.
According to the works of authors like Koter, politicians must build on pre-existing networks between leaders and their followers. Not all local networks are the same, but also do not all politicians have the same access to these networks. Thus, the relationships that actually form on the ground are determined by the availability of local leaders, by the choice of a politician to use these as a resource, and by the access that he or she is granted.
While previous contributions have been interested in the effect of these networks on electoral outcomes (networks as independent variables), this paper looks at the MP as a part of the of the local network structure. Using local network structure as a dependent variable, this paper explores the variance in social relations: do the local networks that politicians entertain differ in any systematic way with regard to age, political faction, experience, or social capital? Women, for example, might find it harder to be integrated in local power and patronage structures, and ruling parties might be generally more successful in garnering the support of local leaders since they can make more credible promises to deliver material benefits. And finally, there might be certain categories of politicians that do not seek to build intermediary relations but rather invest into the local party.
To answer these questions, the paper uses original data on the local discussion networks of Members of Parliament (MPs) in Ghana, Togo, and Sierra Leone. Methodologically, descriptive and statistical social network analysis is used.

Author

• Anja Osei, University of Konstanz