Second, the project may have had its principal impact before the first survey in February 2016, in which case the difference between the two surveys might not capture project-induced improvements. We examine the Annual Performance Assessments (APAs) of the project to discern which components show the greatest increase in project measures of institutional performance. In Figure B1 we present the mean scores across project LGAs in each of the performance assessments. Our first round survey was implemented in early 2016, around the fourth APA, while our second round survey happened in 2018, close to the sixth APA. We find that the "Accountability" component of the APA shows a large increase between the 2nd and 3rd APAs, while the other components (Revenues, Infrastructure and Urban Planning) do not show a pattern of concentrated growth before our first survey round. (We discuss the available evidence in more detail in Appendix B.) It could be that had we undertaken a citizen survey in 2013, we may have found that the 18 project LGAs had much lower levels of citizen-survey-based Accountability measures than the 22 non-project LGAs in 2013? What if the project incentivized the 18 LGAs who were reluctant to publicly post their budget information in the absence of these project incentives; what if our 2016 survey measure, compared to this hypothetical 2013 survey measure, shows that Accountability significantly improved, as a result of the project incentivizing the LGAs to reach out to citizens? We cannot rule this out because we do not have survey data from 2013 across both project and non-project LGAs. We find no significant difference between project and non-project LGAs in the 2016 survey measures of citizen engagement targeted by the Accountability component, nor in changes in citizen engagement between 2016 and 2018.

We argue that our two rounds of surveys appear well positioned to capture something proxying a baseline for outcomes in February 2016, before the project was disbursing substantially, and improvements over a two year period as the project is actively implemented. The 2018 Quality Assurance Review (a report that reviews the project’s implementation and is led by an external consultant) indicates that disbursements of project funds were delayed in the early years of the project, with funds starting to flow and investment activities happening only towards the middle of 2017, i.e, the end of the World Bank’s fiscal year 2016/17 (Roelcke et al., 2018). Our survey measures are consistent with this. For example, on a set of questions posed to local government officials about whether disbursements from the central government are timely, responses show significant improvement in April 2018, compared to February 2016, consistent with the consultants’ report. However, there is no difference in this improvement between the project and non-project LGAs.

Third, measuring experience with service delivery is subject to error and reporting biases. For example, the period 2016-2018 in Tanzania is one where a new president took office (in October 2015), announced and implemented several policy measures to crack down on corruption, and strengthened performance norms among government officials. These announcements and actions may have created a perception that things are improving, coloring the survey responses equally in both project and non-project areas. However, our survey is careful to avoid pure perception questions such as degree of “satisfaction” with government performance or agreement/disagreement with whether things are “improving.” Instead, the questions probe for actual 26