We study optimal experimentation by a monopolistic platform in a two-sided market framework. The platform provider faces uncertainty about the strength of the externality each side is exerting on the other. It maximizes the expected present value of its profit stream in a continuous-time...

We study optimal experimentation by a monopolistic platform in a two-sided market. The platform provider is uncertain about the strength of the externality each side is exerting on the other. Setting participation fees on both sides, it gradually learns about these externalities by observing...

We study optimal experimentation by a monopolistic platform in a two-sided mar- ket. The platform provider faces uncertainty about the strength of the externality each side is exerting on the other. It maximizes the expected present value of its profit stream in a continuous-time...

We analyze optimal monetary policy when a central bank has to learn about an unknown coefficient that determines the effect of surprise inflation on aggregate demand. We derive the optimal policy under active learning and compare it to two limiting cases---certainty equivalence policy and...

In this paper we analyze disinflation policy when a central bank has imperfect information about private sector inflation expectations but learns about them from economic outcomes, which are in part the result of the disinflation policy. The form of uncertainty is manifested as uncertainty about...

We study the impact of adaptive learning for the design of a robust monetary policy using a small open-economy New Keynesian model. We find that slightly departing from rational expectations substantially changes the way the central bank deals with model misspecification. Learning induces an...