alternative clusterings of the standard errors, including robust standard errors, allowing them to be clustered by project type within organization (so at the _jn_ level), by project type within sector, and by sector. In all cases, the coefficients of interest, _γ_ 1 and _γ_ 2, remain precisely estimated and statistically di↵erent from zero at conventional significance levels ( _p < ._ 05 throughout).

# **3.3 IV**

Before digging deeper into what drives the _negative_ partial correlation between project completion rates and incentives/monitoring of bureaucrats, we first present additional evidence that this might represent a causal relationship. A chief concern is that management practices are endogenous to organizational performance, so the negative result could reflect that if an organization has low project completion rates, it increases the provision of incentives/monitoring to its bureaucrats.

We address such reverse causality using an IV strategy that exploits the fact that similar interviews on management practices had previously been undertaken for a subset of the same organizations in 2013, by one of us in a separate and independent study [Williams 2015]. While these interviews were primarily qualitative and on a much smaller scale (based on one or two senior bureaucrats in each organization), they also took a similar semi-structured format and adapted the approach of BSVR, coding the quality of each management practice on a 1-5 scale, with overall organization z-scores compiled in the same way.

Table A4 details the questions on management practices administered in the 2013 interviews. While the same six topic areas were covered as in our 2015 survey, there is a far more limited set of questions on the topic of bureaucrat roles, which meant it was not possible to reconstruct a measure of CS-autonomy from the 2013 data. We therefore focus on exploiting the earlier measure of management practices related to the provision of incentives/monitoring, as measured two years prior to the main management and project completion measures used for the core analysis. We instrument current practices related to incentives/monitoring with the historic practices along the same dimension of management. The exclusion restriction requires that past management practices related to incentives/monitoring only impact current project delivery through their persistent e↵ects on management practices on this dimension.

Table 4 shows the results. Column 1 replicates our baseline OLS specification in the subsample of 18 organizations for which management practices related to incentives/monitoring are available from 2013 (and so can be used for the IV strategy).<sup>15</sup> Our baseline results continue to hold, b b although the e↵ect sizes are smaller than in the full sample ( _γ_ 1 _,OLS_ = _._ 04, _γ_ 2 _,OLS_ = _−._ 09), but are both estimated with similar if not greater precision. Column 2 shows the first stage and demonstrates the strength of the instrument: the first stage F-statistic is over 100. There is high

> a specification analogous to (1) but using a fractional regression to account for the fact that project completion rates lie between zero and one. Finally, in Column 9 we control for project-sector level fixed e↵ects (so allowing for sector specific impacts of project types).

> 15As we only have 18 organizations in these specifications, we do not control for general and capital controls.

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