A nested bundling strategy creates menus in which more expensive bundles include all the goods of less expensive ones. We study when nested bundling is optimal and determine which nested menu is optimal, when consumers differ in one dimension. We define a partial order on bundles by (i) set inclusion and (ii) sales quantity when sold alone. We show that, under quasi-concavity assumptions, if the undominated bundles with respect to this partial order are nested, then nested bundling is optimal. We present an iterative algorithm that identifies the minimal optimal menu consisting of a subset of the undominated bundles.

Economists routinely make functional form assumptions on demand curves to derive welfare conclusions. How sensitive are these conclusions to such assumptions? In this paper, we develop robustness measures that quantify the extent to which the true demand curve must deviate from common functional form assumptions in order to overturn a welfare conclusion. We parametrize this variability in terms of the gradient and curvature of the demand curve. By leveraging tools from information design, we show that our measures are easy to compute. Our measures are also flexible and easy to use, as we illustrate through empirical applications.