10 pairs of constituencies in this set aggregated to the local government level, leaving 345 constituencies under study.<sup>11</sup> For each of the 345 representatives I study, I have assembled biographies that outline their demographic and political characteristics (such as their party affiliation), their educational qualifications and work experience, and the results of their elections in 2003 and 2007.<sup>12</sup> Table 1 provides descriptive statistics for the political constituencies we study. The vast majority of the politicians under study are men, with a mean age of 48, and 16 years of education (equivalent to a Bachelor’s degree). The average population of a constituency is 370,000. This population is split, on average, between two local governments, which is the most basic administrative unit of government in Nigeria. The local nature of congressional politics implies that local public project provision is central to the success of a representative’s time in office. National Assembly politicians do not face term limits, implying they have an ongoing incentive to provide public projects to bolster their re-election chances. A quarter of the politicians whom I study are already serving a second term.

The political competition faced by representatives is relatively heterogeneous across constituencies.<sup>13</sup> While the mean margin of victory is 0.33, there is substantial heterogeneity across the country. As Figure 1A shows, I observe constituencies subject to the full distribution of levels of political competition.<sup>14</sup> The heterogeneity in competition is not concentrated in one area of Nigeria. As Figure 1B indicates, there are large differences in competition between proximate constituencies. The average differential in margin of victory across neighboring constituencies is 20 percentage points. Thus, political incentives vary substantially across constituencies with similar geographic characteristics.

I also collected data on whether these representatives stood for and won the election held mid-way through 2007 after budgeting had been completed and implementation of projects begun. Election results were unavailable directly from INEC for 2007, and so I used the data published by Carr (2011) collected from the INEC website as it was published in real time (and quickly taken down thereafter).

To further characterize a representative’s constituency, I use the largest household survey ever undertaken in Nigeria, the 2005 Core Welfare Indicators Questionnaire (CWIQ). This was a cluster-randomized household survey run by Nigeria’s National Bureau of Statistics, representative at the local government level. The CWIQ survey was implemented at the end of 2005, at the same time as politicians were making delegation decisions in the first round of standing committees, and it therefore provides a baseline profile of the constituencies that I study. Using this survey, I create constituency-level averages for indicators of

> 11I do not have evaluations of project outcomes for 10 constituencies, so I exclude these constituencies in the analysis. I describe the sampling of projects in the Appendix. The constituencies of 10 representatives are smaller than a local government area, the smallest administrative unit in my data on public projects. I therefore aggregate constituencies to their local government, leaving 345 federal constituencies to be studied. The characteristics and winning vote shares of the representatives who share local governments are very similar. I therefore allocate the constituency to that one of the two representatives who is first on the nominal roll of the election records. The core results of the paper are qualitatively unchanged if I include or exclude the projects located in local governments with multiple representation or use the second of the two representatives.

> 12The Appendix details the construction of these biographies. I collected election data from the Independent National Electoral Commission on the returns for each of the elections in 2003 (when the politicians I study were voted into power). These are data that were published as the official roll of the national elections.

> 13My measure of political competition is 1 minus the margin of victory, defined as the winner’s vote share minus the runner’s up vote share. It represents the proximity of the runner up to the winner. Such a measure is used by Besley and Burgess (2002), Lee (2008), and Da Silveira and De Mello (2011).

> 14The distribution of political competition across constituencies in other countries is similarly diverse. For the US, recent election data are surprisingly similar to that of Nigeria. The average margin of victory for House elections in 2012 was 0.32, and constituency contests spanned the full distribution of political competition. For the UK, the margin of victory varies continuously between 0.01 and 0.58, with a mean of 0.19. There is substantial heterogeneity across neighboring constituencies, as in my data. Comparing this context to other developing country democracies, India is closer to the UK context, with the margin of victory spanning 0.01 to 0.61, with a mean of 0.12. Ethiopia, the second largest democracy in Africa after Nigeria, has an average margin of victory of 0.5 and varies between 0.01 and 0.96. (All figures are authors calculations based on election statistics from relevant election bodies).

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