Abstract

\iflatexml \documentclass[a4paper, 11pt]{article} \fi \usepackage[T1]{fontenc} \usepackage{graphicx} \usepackage{amsthm, amsmath} \usepackage{amsmath} \usepackage{natbib} \usepackage{graphicx} \usepackage{mtpro2} \renewcommand{\figurename}{Figure} \renewcommand{\theequation}{} In this paper we turn our attention to comparing the policy function obtained by \verb|\cite{bw2002}| to the one obtained with adaptive control methods. It is an integral part of the \textit{optimal learning} method used by Beck and Wieland to obtain a policy function that provides the optimal control as a feedback function of the state of the system. However, computing this function is not necessary when doing Monte Carlo experiments with adaptive control methods. Therefore, we have modified our software in order to obtain the policy function for comparison to the BW results.\\ \\ \emph{\textbf{Keywords}} Active learning, dual control, optimal experimentation, stochastic optimization, time-varying parameters, numerical experiments.\\ \\ \emph{\textbf{JEL Classification}}: C63, E61.