This dissertation consists of two related chapters. In Chapter 1, I examine the effects of measurement errors in price expectation and shopping plans on the estimates of a consumer demand model. To this end, I estimate a household level store choice model in the supermarket industry. Errors in forecasting expected costs of planned shopping lists are prevalent in estimating a demand system for multi-product retail stores because price beliefs and shopping plans of individual households are not observed by researchers. Previous studies parsimoniously use realized shopping bundles as a proxy for the unobserved shopping list and assume homogeneous price expectation for all households and over the entire sample periods. This measurement errors introduce attenuation biases in the estimates of price elasticities toward zero.I improve on this approach in earlier studies by modeling endogenous shopping bundles by estimating good-household-time specific good purchase probability and quantity of purchased goods. I also construct household-time-store-good specific price expectation based on households' previous trips to the store. I show that heterogeneity in price expectation substantially reduces attenuation biases in the estimates of own price elasticities. In Chapter 2, I estimate the effects of pricing on storewide profitability in the supermarket industry. I use the estimated store choice model in Chapter 1 to measure the effects of price promotions on store choice decisions. Household-, time-, store-, and good-specific price expectation introduced in this model allows me to understand how price changes affect price beliefs of households over time and this facilitates measuring the dynamic effects of price promotions on store sales or profits. A straightforward extension of this analysis is to measure the effects of loss-leader pricing with price advertising of stores.I show that storewide effects of price discounts are larger and last longer when price promotions are offered for a long period and deteriorate over time. Also, price promotions more effectively attract customers to the store when they are applied to a wide variety of products even with a moderate level of price reduction than deeper price cuts over a small group of products. Lastly, feature advertising has substantial effects of boosting store traffics and this result supports the loss-leader stories where deep price cuts in a selected set of products lure customers to the store and improve storewide profits.