Center-West regions are currently not available.<sup>17</sup> We provide further details on the geographical and temporal coverage of the dataset in Table 1. Starting with geographical coverage, our budget execution tables (commitment, verification, and payment) are available for all seven states. The procurement data are less comprehensive: the dataset currently includes no procurement data for SP, and the data for PB and PE include information on tenders and participants, but not on the more disaggregated level of items. In terms of temporal coverage, most of our budget execution data starts in the earlyto mid-2000s, with the exception of PE (2012), PR (2013), and MG (2014), and currently runs until 2021. Once again, data on procurement is less comprehensive and, with the exception of CE (2009-2021), starts in the mid-2010s.

In Table 2 and Table 3, we provide simple descriptive statistics from our public procurement and budget execution datasets, respectively. For procurement, across the six states covered, we observe over 2.4 million unique tenders and almost 800,000 unique suppliers. Since we observe microdata on each tender and often items, we are able to compute statistics such as the share of tenders that are deserted and/or unsuccessful (e.g., no bidders in a competitive tender) and the average number of items listed in a tender. We can also document, for example, that across states approximately 30%-40% of tenders are not competitive auctions – meaning they are directly awarded to suppliers by means other than an auction – but in terms of total purchase value these non-competitive tenders always represent less than 20% of total amounts. This is consistent with the fact that, similar to other countries, Brazilian law allows small purchases to be performed without competitive auctions (Fazio, 2022). We can also compute measures of competitiveness in tenders, such as the number of participants per tender - the average fluctuates between two and four across the municipalities in our sample. The dataset often contains unique identifiers for each supplier, which in Brazil vary if the supplier is an individual or a firm, allowing us to compute the share of suppliers identified as firms (which vary substantially across states, from less than 60% in CE and PB to over 80% in MG).

Statistics for the budget execution dataset are presented in Table 3. Our budget execution dataset includes over 880 million observations - over 250 million commitments, around 300 million verifications and over 300 million payments. For all three stages of the budget execution, we present the total number of observations and the total number of _distinct_ events – in some cases, we are unable to assess whether two commitment observations, for example, refer to the same commitment or not. In those cases, we set our respective identifier variable to missing to flag to users that we are unsure whether these are unique events that can be tracked across datasets. Using the budget classification discussed previously, we estimate that between 25%-35% of total budget commitment events are related to the procurement of

> 17Municipalities that are in our sample are slightly richer and more educated than those that are not. In 2019, the average GDP per capita (literacy rate) in our sample was 26.8 thousand BRL (87.7%), while in the municipalities that are not in our sample it was 22 thousand BRL (82.5%). Population size, however, does not differ across the samples (37.7 thousand inhabitants in both).

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