records of urban planning, internal audits, establishment of tender boards for public procurement, recruitment of key state personnel, adoption of technologies for property tax management, and increase in local own-source revenues, among others. The size of fiscal grants to local governments under the project are conditional on their performance in achieving institutional outcomes, as assessed by an independent third-party. On average, the fiscal grants represent about 15 percent of total revenues for local governments in 2011.<sup>3</sup> In addition to the performance grants, these projects also include mechanisms to help local governments with advice and technical assistance on how to plan, audit, procure, recruit personnel, use technology, increase revenue collection, etc. In other words, local governments receive technical support in all the areas of institutional performance on which they are being assessed.

This paper provides evidence on whether institutional outcomes targeted by the capacity building project in Tanzania are different across local governments that received the project and those that did not. Since the selection of project local governments is not amenable to randomization in these types of programs,<sup>4</sup> any evaluation design has to contend with both observable and unobservable initial differences between treatment (those receiving the World Bank capacity building project) and comparison (those not receiving the project) Local Government Areas (LGAs). To address these issues we use a difference-in-differences method to estimate the project impact by comparing outcomes between project and non-project LGAs over time. The difference-in-differences method does not require treatment and comparison areas to be statistically identical at the start of the program, but it does require that the two groups would develop at similar rates in the absence of the project. This is often called the "parallel trends" assumption.

The evidence comes from 40 Local Government Areas of Tanzania over the period 2016-2018, of which 18 LGAs had been selected in 2013 to receive the World Bank capacity building project. The project team indicated at the outset that the selection of these 18 LGAs was purposive, based on negotiation between the World Bank and the Government of Tanzania (World Bank, 2012). Thus, we knew at the outset that these 18 LGAs were likely to be systematically different from other LGAs in the country on both observable and unobservable variables. To minimize these differences, we worked closely with the government and the World Bank project team to identify comparable LGAs (22 non-project LGAs were identified to serve as comparators) which would not be receiving the project, complementing this identification process with propensity score matching. The difference-in-difference strategy we adopted was supported at the outset by evidence that in the years preceding the project, project and non-project LGAs had similar growth in local, "own source" revenues, a key measure of state capacity. This similar growth in the absence of the intervention is the fundamental assumption behind the difference-in-differences estimation strategy.

We then implemented two rounds of surveys across these 40 LGAs (18 receiving the project and 22 comparators) of 474 government officials and 2,998 citizens, two years apart, during a

> 3Total revenue includes own source revenues and transfers from the central government. 2011 is the most recent year for which we have revenue data disaggregated at the LGA level.

> 4We discuss the infeasibility of randomization in the section describing the institutional context.

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