A small literature examines the role of the IFC as an investor and development institution. Dreher et al. (2019), investigating the link between IFC loan allocation and board membership in the institution, found a positive relationship between political influence and lending decisions, and Taussig and Delios (2015), using data from the IFC’s investment in private equity funds to examine the role of local expertise and performance, found local expertise to improve performance more in countries with weak contract enforcement institutions. Kenny et al. (2018), analyzing the countries targeted by IFC investment between 2001 and 2016, noted a shift in allocation from lowto middle-income countries. Although none of these papers report on returns obtained by the IFC, Desai et al. (2017) studied the relationship between IFC project returns and ESG risk factors since 2005, finding no evidence that better ESG performance is linked to improved financial performance.

**Potential Selection Bias** The IFC equity portfolio data enable us to avoid two forms of selection bias that typically hamper analysis of the performance of an asset class. A first source of selection bias is survivorship bias, that is, when successful investments or funds are more likely than failures to appear in a data set (Carhart et al. 2002) discuss this in the context of the mutual fund industry). Because the data include all of the IFC’s equity investments, including write-offs, comparisons of investments within the portfolio will not be affected by such bias. Another version of survivorship bias would be if its performance influenced the probability of the IFC disclosing its returns. The IFC, however, has had a longstanding policy of disclosing performance in annual reports.

A second potential source of bias is infrequent valuation, as when an investor values an investment only upon a successful initial public offering (IPO) or after a company completes a successive round of fundraising (Cochrane 2005 discusses this in the context of venture capital). Because valuations may be positively correlated with these events, ignoring investments that have not gone public or raised further funds could lead to an upward bias in average performance. Our estimates are not subject to such bias because (i) the majority have already exited, and (ii) we include the mark-to-market net asset values of all unrealized investments on the same date (Gompers and Lerner 1997). Nonetheless, because mark-to-market valuations are themselves challenging to do correctly (Jenkinson et al. 2013, Brown et al. 2013), in our regression specifications we restrict the sample to mature investments by excluding the ten most recent vintage years (2010-2019). This ensures that our results are not driven by mark-to-market valuations that are more difficult to determine given the youth of the investment. For robustness, we also report results restricted to the sample of realized investments (Tables A6 and A9).

Management, an affirmation that identifies them as impact investors. The leverage ratio is calculated as total assets divided by total equity using values from annual reports. For the European Investment Bank, total equity is the sum of accruals and deferred income, provisions, subscribed capital, reserves, and profit for the financial year.

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