  I describe a method for estimating agents' perceived returns to investments
that relies on cross-sectional data containing binary choices and prices, where
prices may be imperfectly known to agents. This method identifies the scale of
perceived returns by assuming agent knowledge of an identity that relates
profits, revenues, and costs rather than by eliciting or assuming agent beliefs
about structural parameters that are estimated by researchers. With this
assumption, modest adjustments to standard binary choice estimators enable
consistent estimation of perceived returns when using price instruments that
are uncorrelated with unobserved determinants of agents' price misperceptions
as well as other unobserved determinants of their perceived returns. I
demonstrate the method, and the importance of using price variation that is
known to agents, in a series of data simulations.
