there is no evidence of underlying unobservables selecting politicians across sectors. There is evidence that members of the agriculture committee face more significant political competition in their constituencies. It is therefore important for us to be able to instrument for any remaining concerns using pre-existing qualifications. I will also check the robustness of the core results for this deviation from the general pattern that qualifications are the dominant determinant of committee membership.

One concern is that constituency characteristics indirectly influence committee membership by determining the sector of a representative’s qualifications and experience.<sup>24</sup> For example, a politician from an arid region of Nigeria may enter into the water sector. It may then be more challenging to implement water projects in that region, thus linking sector of experience and project implementation.

To investigate this, Table A4 investigates the determinants of a politician’s sector of qualifications and experience by estimating a SUR model of sector expertise on individual and constituency characteristics. I create dummies for each of the sectors into which a politician could have specialized. These take the value 1 when the politician has specialized in that sector, and zero otherwise. To represent the past constituency characteristics on which politicians made their career decisions, I use previous survey data collected at the time most politicians were making their career choices. The mean politician is 48 years of age in 2006, implying that they made primary career decisions during the late 1970s. In 1980, Nigeria undertook its first systematic household survey, the National Integrated Survey of Households (NISH). The 1980 variables are strong predictors of contemporary constituency characteristics, providing a validation of both sets of household data, collected a quarter of a century apart. I therefore coded state-level averages from the NISH survey for the variables closest to those in the core analysis and associated them with the corresponding politician in the data set.<sup>25</sup> Table A4 presents the results of how constituency characteristics in 1980 impacted on the sector decisions of the politicians I study. It suggests that there is almost no evidence that individual and constituency characteristics determined the sector into which a politician specialized. Almost none of the coefficients are significant at the usual levels.<sup>26</sup> Another quantitative check comes from comparison between the Senate and House. If constituency-level characteristics determined the sectors into which representatives selected, I should find that senators from the same areas have selected into the same sectors. I find this is rare. Only 13 percent of representatives are on a committee of the same sector as their senator. For any particular committee, that figure is at most 3 percent. This is consistent with the fact that within a state, House representatives specialize into distinctive sectors.

The totality of the evidence points towards the House Selection Committee determining committee membership based on factors that are exogenous to constituency-level characteristics that might have significant impacts on project implementation or the choice of organization delivering public projects.<sup>27</sup> Thus, as Payne (2003) finds substantial evidence for arbitrariness in the makeup of US congressional

> 24As complementary to the formal tests of this, I note that Nigeria only became a democracy in 1999, such that almost all of the qualifications on which the Selection Committee made their decisions were gained well before the standing orders were even conceptualized. When they made their career decisions, politicians would not have known how the House standing orders would be designed or perhaps whether Nigeria would have a National Assembly at all.

> 25Where new administrative units have formed, I matched the politician to the data that most closely corresponded to their constituency.

> 26I have also undertaken this analysis with the contemporary CWIQ survey and find similar results to those in Table A4 in that no pattern of career choice determination is observable. This is indicative that voters are not choosing politicians to represent them that have qualifications in their sector of greatest need.

> 27To what extent would unobservable factors not picked up in the tests be able to play a significant role in the analysis? I can explore the potential for unobservable factors to reduce the estimates in this section to 0 using the correction for unobserved heterogeneity described by Altonji et al. (2005) and Oster (2013). Based on an intended R-squared of 0.8, I find that explanatory variation in unobserved factors would have to be roughly 4 times as large as the observed variation in the controls. Given that we see almost no evidence of sorting in the observables, this provides additional assurance that membership is a valid instrument in this setting.

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