The celebrated Taylor rule provides a simple formula that aims to capture how the central bank interest rate is adjusted as a linear function of inflation and output gap. However, the rule does not take explicitly into account the zero lower bound on the interest rate. Prior studies on interest rate selection subject to the zero lower bound have not produced derivations of explicit formulas. In this work, Taylor-like rules for central bank interest rates bounded below by zero are derived rigorously using a multi-parametric model predictive control framework. This framework is used to derive rules with or without inertia. The proposed approach is illustrated through simulations. Application of the approach to US economy data demonstrates its relevance and provides insight into the objectives underlying central bank interest rate decisions. A number of issues for future study are proposed.
Taylor rule zero lower bound liquidity trap model predictive control multiparametric programming