The present essay analyses the performance of a central bank to achieve the learnability of parameter values that govern the Phillips Curve (PC) equation while trying to stabilize the inflation rate. The present essay shows the ability of policymakers to achieve both objectives simultaneously. Using a Recursive Least Squares (RLS) algorithm to model the learning process performed by the central bank, it will iteratively estimate the parameters, which account for the level of persistence in inflation and the impact of increases in the policy interest rate on the inflation rate in the economy. Various simulation scenarios will confirm that the central’s bank estimates, with the
addition of sufficient exogenous variation, can progressively converge to their actual mean values. Learnability will also be shown to be robust to the inclusion of time-variability in the structure of parameters that compose the PC equation.