in a given country-sector is not exogenous, the identification of causal effects is impaired by the fact that macro data do not allow for determining if private lending would have happened even without MDB involvement. Our approach, based on more granular loan-level data, has the advantage of absorbing all time-varying country- and sector-specific factors which could drive MDB and private sector lending via a large set of fixed effects. In particular, by exploiting country-sector level data, we are able to control not only for country- and year- fixed effects, but also for countrysector, country-year, and sector-year fixed effects; hence, we greatly diminish the possibility of omitted variable bias and increase accuracy in the estimation of the mobilization effects.

Our results—based on regressions at the country-sector-year level—indicate that the volume of syndicated lending, the average number of lending banks per loan, and the average loan maturity increase in the years following the presence of a syndicated loan with MDB participation in a given country-sector pair.

To mitigate concerns of reverse causality, we show (i) descriptive evidence that MDBs tend to be among the first to enter a given country-sector, and (ii) formal evidence of the lack of anticipation effects. Then, we run a number of robustness tests to address lingering concerns about the omitted variable bias, which could potentially affect our results, as long as there are confounding factors driving both MDB and private bank lending. In particular, we show that including a large set of confounding factors in the baseline model—the presence of the largest global banks, Chinese lending, aid flows, corporate bond issuances, and value added growth in the country-sector pair— does not affect the significance or the size of the estimated MDB mobilization effects. In addition, we control for sector-specific linear and quadratic trends and identify the effects in deviation from trend, and we further control for unobserved heterogeneity computing the Oster (2019) bounds.

We perform a number of extensions. First, to have a better sense of the macroeconomic implications of our results, we exploit the information on the volume of MDB lending to estimate the MDB lending multiplier. We find that for each dollar that MDBs invest through syndicated loans, they are able to mobilize about seven dollars in syndicated lending by private banks over a threeyear period. These are economically meaningful effects, which suggest that MDBs could actively contribute to mobilizing resources towards meeting the ambitious goals of the 2030 Development Agenda. Second, by estimating total mobilization effects, which include direct and indirect effects, we find evidence suggesting that MDBs can attract private flows both directly and indirectly.<sup>4</sup> Third, we deal with the concern that the mobilization effects on lending could be partially or com-

> 4 We consider direct mobilization as the financing from a private entity that directly participates in a syndicated loan with the MDB, and indirect mobilization as the financing from a private entity mobilized in connection with a specific MDB activity but lent to the borrower through other syndicated loans.

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