Before revision:  " Agents' stationary equilibrium learning rules incorporate past information by taking linear combinations of other agents' past estimates (as in the simple DeGroot heuristic), and we characterize the coefficients in these linear combinations . We discuss how the resulting tractability is useful for structural estimation of equilibrium learning models and testing against behavioral alternatives .
After revision:  " Agents' stationary equilibrium learning rules incorporate past information by taking linear combinations of other agents' past estimates (as in the simple DeGroot heuristic), and we characterize the coefficients in these linear combinations .