We compare the ESG ratings of MSCI, a global rater, with those of SINO, a local Chinese rater, to evaluate their effectiveness in capturing ESG risks within the Chinese context. Using ESG issues revealed in negative incidents as a proxy for ESG risk, we find that the ratings from the two raters often diverge, with SINO generally outperforming MSCI in predicting ESG risks in China. This divergence is more pronounced for firms with extensive ESG disclosures and when there are significant differences in how the raters define and measure ESG issues. Distance-based information asymmetry does not appear to play a significant role in explaining the performance gap. The advantage of local raters likely stems from their flexibility in tailoring methodologies to reflect country-specific nuances. In contrast, global raters adopt consistent methodologies to meet investor demand for comparability, but this approach may inadvertently reduce their relevance for capturing localized ESG risks. Data Availability: Data are available from sources identified in the text.

We study whether sell-side financial analysts’ social ties to firm management help them discern firms’ financial reporting frauds and, upon such detection, how the connected analysts disseminate the information. Using unique data from China, we find that, although unconnected analysts do not manifest a significant change in their likelihood of covering the fraud firms nor in issuing more downgrade stock ratings, connected analysts are significantly more likely to drop coverage right after these firms’ first annual reports containing fraudulent information. Meanwhile, mutual funds with a trading commission relationship to these connected analysts (i.e., client funds) are significantly more likely to unload their holdings of fraud firms than nonclient funds after these firms’ first fraudulent annual reports. Overall, the evidence suggests that analysts with social ties to firm management have early access to bad news and choose to privately communicate the negative information to their clients. Data Availability: All data used in this article are publicly available.