Bundling against Learning

A monopolist sells multiple goods to an uninformed buyer. The buyer chooses to learn any one-dimensional linear signal of their values for the goods, anticipating the seller’s mechanism. The seller designs an optimal mechanism, anticipating the buyer’s learning choice. In a generalized Gaussian environment, we show that every equilibrium has vertical learning where the buyer’s posterior means are comonotonic, and every equilibrium is outcome-equivalent to nested bundling where the seller offers a menu of nested bundles. In equilibrium, the buyer learns more about a higher-tier good, resulting in a higher posterior variance on the log scale.