borrow to increase production to satisfy the procurement demand. Such an interpretation may also be consistent with the initial crowding-out of sales to the private sector (if firms faced shortrun capacity constraints or decreasing returns to scale in production) and with the medium-run crowding-in of sales to the private sector (if firms invest in production capacity to serve the extra demand for the public sector that can be later used for the private sector operations). The second interpretation is that procurement represents a _credit supply shock_ at the firm level. This will be the case if procurement contracts can be pledged for extra borrowing and a sizeable fraction of firms doing procurement are credit-constrained. This would explain why the increase of credit at impact does not require collateral to be posted. The existence of credit constrains for firms participating in procurement is consistent with the short-run crowding-out of sales to the private sector (as financially constrained firms do not have the financial capacity to completely serve both demands) and with the crowding-out being stronger for firms more likely to be financially constrained. The medium-run crowding-in of sales to the private sector is also consistent with binding credit constraints (procurement gives firms extra profits, which can be saved and used to expand production capacity in the future).

While both interpretations are plausible, our results point to the _credit supply shock_ interpretation playing a relevant role because (i) the short-run increase in credit is limited to non-collateral credit, (ii) we provide additional evidence on the acceptance of loan applications below, and (iii) the short-run crowding out of private sales being larger for firms more likely to be constrained indicates that financial frictions affect procurement firms.<sup>12</sup> However, to gauge the relative importance of the credit _demand_ and _supply_ interpretations, we need a formal model structure as that presented in Section 4.

Appendix B provides further evidence on the relationship between firms’ participation in procurement and credit growth. We summarize the evidence here.

**Procurement and credit using quarterly frequency.** To provide tighter identification of the effect of procurement on credit, in Appendix B.2 we exploit higher frequency credit data and estimate the procurement effect on credit using quarterly data. Importantly, these specifications allow us to control for _firm_ × _year_ fixed effects, which absorb all firm characteristics, observable or unobservable, varying at the yearly frequency. First, we find that winning a procurement contract is associated with an annualized increase in credit of around 5.5 pct, which is similar in terms of magnitude to the effects on impact, i.e., _h_ = 0, estimated above in Section 3.1. And second, we also find that the effect is entirely driven by non-collateral credit.

**Winners vs. the rest.** In Appendix B.3, we use the sub-sample of procurement projects where we have information on all bidders as well as the final ranking (see Appendix A.2 for details on this

> 12Also, indirect inference motivated by our structural model, as seen in Section 5, provides evidence for procurement earnings relaxing firms’ credit constraints.

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