Optimal Myopic Information Acquisition
55 Pages Posted: 13 Mar 2017
Date Written: August 14, 2017
We consider the problem of optimal information acquisition from many correlated information sources. Each period, the DM jointly takes an action and allocates a fixed number of observations across the available sources. His payoff depends on the actions taken and on an unknown state. In a canonical setting--jointly normal information sources--we show that the optimal dynamic information acquisition rule proceeds myopically after finitely many periods. If signals are acquired in large blocks each period, then the optimal rule turns out to be myopic from period 1. These results demonstrate the possibility of robust and "simple" optimal information acquisition, and simplify the analysis of dynamic information acquisition in a widely used informational environment.
Keywords: learning, information acquisition, dynamics
JEL Classification: D81, D83, C44
Suggested Citation: Suggested Citation