find a doctor within the North-East zone from the ruling party, there is typically very little room for other factors to play a role. This was confirmed by interviews with the secretaries of the standing committees and with external academics.

# **A.4 Constituency controls**

To control for a range of constituency-level characteristics, I use data from the largest household survey ever undertaken in Nigeria, the 2005 Core Welfare Indicators Questionnaire (CWIQ). The CWIQ survey targeted 77,400 households, 100 in each local government area. I define a battery of controls from the CWIQ survey along the following lines. I construct constituency-level means and standard deviations of the following indices: the proportion of poor in the constituency, measured by a national poverty index, the average years of education of the household head, the proportion of constituents with access to potable water, the average time in minutes to the nearest primary school, and the average journey time in minutes to the nearest secondary school. These indices reflect the sectors under which the majority of the projects in my data fall.

One may also expect politicians to respond to recent investments in their constituency. For example, a politician may feel less inclined to invest in an area that has recently received substantial public projects investments. To reflect the frequency with which constituents have benefited from a public project of the named type in the five years preceding the survey, I also construct indices of whether constituents have received: construction of electrification infrastructure, rehabilitation of electrification infrastructure, a well/borehole, construction of piped water infrastructure, rehabilitation of piped water infrastructure, sanitation, school construction project, school rehabilitation, health facility construction, health facility rehabilitation, road construction, tarring/grading of roads, transportation services, and agricultural-inputs schemes.

Finally, there may be complementarities between the economic environment and public investments. For example, greater access to credit may lead citizens to demand public projects that will facilitate their use of that credit. I therefore create indicators of changes in opportunities for employment, the availability of agricultural inputs, number of buyers of agriculture produce, the availability of extension services, the availability of credit facilities, and the availability of consumer goods.

# **A.5 Defining complexity indicators**

Data on the complexity of government projects are not collected by the Nigerian Government, nor is it a part of the OPEN data set. To create this data, I worked with a pair of Nigerian engineers familiar with the OPEN projects and a number of international researchers working on project technical complexity to define a relevant set of indicators. I followed the perspectives on complexity suggested by Remington and Pollack (2007), by asking the engineer-assessors to individually assess projects along the following five topics, each with its own set of indicators.

_Structural complexity_ stems from the scale of different interconnected tasks and activities. The indicators associated with this topic capture structural aspects such as project size and the number of inputs required for production. They also capture issues in raw material and labor supply, and the ease with which any necessary specialized skills and equipment can be sourced. _Temporally complex_ projects are those in which production involves uncertainties. Hence there are indicators for uncertainties in design and implementation. _Technically complex_ projects are those in which production has ambiguous risks, namely their uncertainties are not well understood. Hence some indicators capture ambiguities in design 26