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Welcome Tp CRETA! Contact Us at : +886.2.3366.1072


We develop a tractable identification approach for strategic network formation models that accommodate both strategic link interdependence and individual unobserved heterogeneity (fixed effects). The key challenge in this setting is that endogenous network statistics (such as the number of common friends) enter the link formation equation, while the mapping from model primitives to equilibrium network structure is generally intractable to characterize and compute. Using a ``bounding-by-c'' technique, our approach circumvents this difficulty by treating endogenous covariates as random variables and exploiting monotonicity restrictions to extract identifying information without requiring characterization of the equilibrium. We derive a system of identifying restrictions based on subnetwork configurations: leading tetrad-based restrictions achieve complete elimination of all individual fixed effects, triad-based restrictions that only partially difference out fixed effects, and general weighted cycle-based restrictions.
https://mingliecon.github.io/