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- Given any guess of θ, we can solve for ν. To estimate θ, we write the problem using mathematical programming with equilibrium constraints (MPEC) following Su and Judd (2012). Let M(θ; c, w) be a minimum distance estimator given the parameterization of cjs, such as using least absolute deviations or least squares. The MPEC problem is to solve min θ,c M(θ; c, w) s.t. FOC(c, θ ; w, x, p) = 0. Critically, we must specify the components entering w as this is the only way to incorporate store-level covariates into the estimation routine. This is in contrast with most of the literature, where store-level costs are first recovered and then regressed on covariates. With our drywall data, we include: driving distance from the closest plant via chain distribution, local retail wages, and product-specific intercepts.31
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