Among the controversies in corporate governance, perhaps none is more heated or widely debated across society than that of CEO pay (Larcker & Tayan, 2019). How CEO pay is determined, and the performance implications of CEO pay is an issue of first-order importance. Efficient contracting (Gabaix & Landier, 2008; Murphy, 1999) and managerial power (Bebchuk & Fried, 2004) have been advanced as the two main explanations for the high level of CEO compensation and the weak links between CEO compensation and firm performance. While both are widely accepted, neither explanation is fully consistent with the available evidence (Frydman & Jenter, 2010). Much remains to be known about the determinants of CEO pay (Core, Holthausen, & Larcker, 1999), and the precise channels by which executives and boards influence CEO pay (Engelberg, Gao, & Parsons, 2013).

Recent studies have documented that geography has significant effects on corporate decisions and outcomes.1 Kedia and Rajgopal (2009) find that geographically-proximate firms adopt similar policies in broad-based option grants. They argue that this arises because geographically-proximate firms are exposed to the same local market conditions and managers at neighbouring firms engage in social interactions. Dougal, Parsons, and Titman (2015) find a high correlation in the capital investment of neighbouring firms, even those in different industries. They suggest that one reason for correlated investment is that local social networks allow managers to share ideas. Parsons, Sulaeman, and Titman (2018) find that geographic variation in social norms accounts for a large proportion of the cross-sectional variation in financial misconduct across major US cities. The evidence from these and other studies on the role of geography suggests that CEO compensation may be correlated among neighbouring firms, over and beyond what economic fundamentals warrant. However, the existence of, reasons for, and consequences of spatial correlation in CEO compensation remain under-explored. Our paper aims to fill this gap.

An empirical challenge in investigating spatial effects in corporate decisions is that the interdependence in the cross section of neighbouring firms makes ordinary least squares (OLS) an inconsistent estimator.2 Prior studies typically regress a firm-level outcome variable, such as CEO compensation (Bouwman, 2013) and corporate investment (Dougal et al., 2015), on the weighted average of that variable corresponding to the neighbouring firms. This approach is problematic, because it overlooks the “spatial lag” among neighbouring firms, and the autoregressive disturbance term (Anselin, 1988). We address such endogeneity concerns by using spatial econometric models, which are well suited for handling both types of interdependence (Kelejian & Prucha, 1998, 1999).3 More importantly, by focusing on how spatial correlation in CEO pay is affected by CEOs’ local social networks, corporate governance, as well as managerial power, and by examining the performance implications of spatial correlation in CEO pay, we shed light on the nature and consequences of spatial spillovers in CEO pay.