ABSTRACT The estimation of gravity models of internal (aggregate) place-to-place migration is plagued with endogeneity (omitted-variable) biases if the unobserved effects of spatial structure are not accounted for. To address this econometric problem, this paper presents a more general specification of the gravity model, which allows for (bilateral) parameter heterogeneity across individual migration paths—along with (unilateral) origin- and destination-specific effects. The resultant “three-way fixed-effects” (3FE) model is applied for an analysis of interstate migration in Mexico based on cross-sectional data. To overcome parameter-dimensionality problems (due to limited or incomplete information), the 3FE model is estimated using the Generalized Maximum Entropy (GME) estimator. The empirical implications of this new modeling strategy are illustrated by contrasting the 3FE-GME estimates with those for the traditional and two-way fixed-effects (2FE) models. The former are far more plausible and intuitively interpretable than their traditional and 2FE counterparts, with parameter estimates changing in expected directions. The (average) effect of the migrant stock is markedly smaller than usually estimated, providing a more realistic measure of network-induced migration. Migration outflows from centrally located origins have significantly steeper distance decay. Path-specific distance effects exhibit directional asymmetries and spatial similarities.