A standard result in the literature on monetary policy rules is that of certainty equivalence: given the expected values of all the state variables of the economy, policy should be set in a way that is independent of all higher moments of those variables. Some exceptions to this rule have been pointed out by Smets (1998), who restricts policy to respond to only a limited subset of state variables, and by Orphanides (1998), who restricts policy to respond to estimates of the state variables that are biased. In contrast, this paper studies unrestricted, fully optimal policy rules with optimal estimation of state variables. The rules in this framework exhibit certainty equivalence with respect to estimates of an unobserved, possibly complicated, state of the economy X, but are not certainty-equivalent when 1) a signal-extraction problem is involved in the estimation of X, and 2) the optimal rule is expressed as a reduced form that combines policymakers' estimation and policy-setting stages. In general, I show that it is optimal for policymakers to attenuate their reaction coefficient on a variable about which uncertainty has increased, while responding more aggressively to all other variables, about which uncertainty hasn't changed.