We study adaptive learning in a monetary overlapping generations model with sticky prices and monopolistic competition for the case where learning agents observe current endogenous variables. Observability of current variables is essential for informational consistency of the learning setup with the model setup but generates multiple temporary equilibria when prices are flexible and prevents a straightforward construction of the learning dynamics. Sticky prices overcome this problem by avoiding simultaneity between prices and price expectations. Adaptive learning then robustly selects the determinate (monetary) steady state independent from the degree of imperfect competition. The indeterminate (non-monetary) steady state and non-stationary equilibria are never stable. Stability in a deterministic version of the model may differ because perfect foresight equilibria can be the limit of restricted perceptions equilibria of the stochastic economy with vanishing noise and thereby inherit different stability properties. This discontinuity at the zero variance of shocks suggests one should analyse learning in stochastic models. Copyright The Review of Economic Studies Limited, 2003.

Sticky price models featuring heterogeneous firms and systematic firm-level productivity trends deliver radically different predictions for the optimal inflation rate than their popular homogenous-firm counterparts: (i) the optimal steady-state inflation rate generically differs from zero and (ii) inflation optimally responds to productivity disturbances. We show this by aggregating a heterogeneous-firm model with sticky prices in closed form. Using firm-level data from the US Census Bureau, we estimate the historically optimal inflation path for the US economy: the optimal inflation rate ranges between 1 percent and 3 percent per year and displays a downward trend over the period 1977–2015. (JEL C51, D24, D25, E31, E52)