Inflation Targeting in a Learning Economy : An ABM Perspective

This paper investigates the performances of an inflation targeting regime in a learning economy whose functioning is tackled via an Agent-Based Model (ABM). While the structure of our ABM has features in common with those of the New Keynesian canonical modelling framework, we model the individual behaviour of the agents under procedural rationality in the sense of Simon (1971) [Simon, H., The Theory of Problem Solving, in 'IFIP Congress (1)', 1971, pp. 261-277]. Instead of assuming that households and firms fully optimize on an intertemporal basis beforehand, and make use of rational expectations in that respect, we assume that their behaviour is guided by simple rules of thumb – or heuristics – while a continuous learning process governs the evolution of those rules. Departures from the rational expectations equilibrium endogenously arise from that learning behaviour. Finally, the central bank implements an inflation targeting regime via a monetary policy rule. Our aim is then to analyse the interplay between the learning mechanisms operating at the individual level and the features and performances of the inflation targeting regime. In such a setting, we show the prime importance of the credibility of central bank's announcements regarding macroeconomic stabilization outcomes, as well as the beneficial role played by the inflation target as an anchoring device for private inflation expectations. We also demonstrate the potential welfare cost of imperfect public information and contribute to the debate on optimal monetary policy rule under imperfect common knowledge and uncertainty