This paper develops a model of demand estimation in which consumers learn about their true
preferences through consumption experiences. We develop a theoretical model of Bayesian updating,
perform comparative statics over the model, and show how the theoretical model can be consistently
incorporated into a reduced form econometric model. We then estimate the model using data collected
for two quasi-public goods. We find that the predictions of the theoretical exercise that additional
experience with a good will make consumers more certain over their preferences in both mean and
variance are supported in each case.
