Using a text-based measure of geographic dispersion that captures the economic ties between a firm and its geographically distributed economic interests, this study provides evidence that financial analysts issue less accurate, more dispersed and more biased earnings forecasts for geographically dispersed firms. We observe the degree to which a firm has an overlapping distribution of economic centers in comparison to industry competitors and suggest that geographically similar firms have lower information gathering costs and thereby more precise earnings forecasts. Empirical evidence supports this prediction. We further find that the geographic dispersion across the U.S. is less likely to affect forecast precision when a firm has economic activities in states with highly correlated local shocks. Our findings suggest that the effect of geographic dispersion is more pronounced for soft-information environments where information is more difficult to make impersonal by using technological advances. Consistent with the information asymmetry argument, we find that geographically dispersed firms have less comparable and more discretionary managed earnings, have less extensive than industry competitors segment information, are more likely to restate sale segment information, and issue annual and quarterly filings with a delay.