We test whether CEOs working near their childhood homes are less likely than nonlocal CEOs to make myopic decisions. Place attachment theories suggest that people develop mutual caretaking relationships with their birthplaces. Also, executive labor markets face less information asymmetry about local CEOs, resulting in lower pressure on local CEOs for quick profits. Consistent with the prediction, we find that local CEOs are less likely to cut R&D expenditures for beating analyst forecasts or avoiding earnings decreases. In their last year of office, local CEOs are significantly less likely to cut R&D than nonlocal CEOs. The CEO locality effect is stronger when more local business interests are embedded in the firm and when the residents of the CEO's birth state have stronger local social bonds. Local CEOs' longer horizons are consistently manifested in their other decisions, such as paying more state tax and being more socially responsible in business operation.

When emerging market firms disclose relationship-based transactions, they face a trade-off in which greater transparency may help lower their cost of capital at the cost of revealing proprietary information. We find that firms overcome this challenge by relying on analysts within their private networks (i.e., connected analysts) who, through repeated interaction with the firm, can better verify relationship-based transactions. Using Chinese firms, we show that firms with more connected analysts have more accurate consensus forecasts and lower forecast dispersion. When a connected analyst departs and stops covering a firm, the accuracy and informativeness of the unconnected analysts' forecasts decrease, suggesting that information spills over from the connected analyst to analysts outside the network. We find a potential mechanism for this information spillover: communication through common institutional clients, which suggests that embedded financial analysts—those sharing close connections with firms and analysts—serve as a channel for disseminating proprietary, hard-to-verify information. JEL Classifications: G14; G15; M40; N25. Data Availability: Data are available from sources identified in the text.