With the growing recognition of the role played by geography in all sorts of economic problems, there is strong interest in measuring the size and scope of local spillovers (i.e., simple anonymous agglomeration or congestion effects, or more complicated interactions between individuals or firms of specific types). It is well-understood, however, that such spillovers cannot be distinguished from unobservable local attributes using just the observed location decisions of individuals or firms. We propose an empirical strategy for recovering estimates of spillovers in the presence of unobserved local attributes for a broadly applicable class of equilibrium sorting models. This approach relies on an instrumental variables strategy derived from the internal logic of the sorting model itself. We show practically how the strategy is implemented, provide intuition for our instrumental variables, and discuss the role of effective choice-set variation in identifying the model, and carry-out a series of Monte Carlo experiments to demonstrate the instruments' performance in small samples.