This dissertation includes three chapters on estimating structural economics models. My research focuses on empirically study consumers' utility from different products, the impact of network effects on consumers' demand for products, and multi-network firms' dynamic pricing strategies. The three chapters share the same feature of estimating a discrete choice demand model, but differ in the static versus dynamic setting and the underlying economics question and strategic behaviors that I'm interested.Chapter 1"The Operating System Network Effect and Telecom Carriers' Dynamic Pricing of Smartphones."The utility a consumer realizes from owning a smartphone increases with its operating system (OS) network size. Due to this OS network effect, multi-network telecom carriers have a different pricing strategy for smartphones than the single- network manufacturers in a dynamic environment. While manufacturers choose higher prices for larger networks, carriers, who can internalize competition across OSs, have incentives to choose lower prices for larger networks. The carriers' pricing strategy contributes to the increasing smartphone users and OS concentration. In this paper, I first analyze a theoretical model to compare the pricing strategies of the carriers and manufacturers. Then I design a structural model of consumers' demand and the carriers' dynamic pricing game for smartphones, and empirically study the impact of the OS network effect and carriers' two-year contract policy on the smartphone market penetration and OS concentration. I estimate the model using product level data from August 2011 to July 2013 in the US. I deal with the empirical challenges of dynamic prices for multi-product carriers, high dimension continuous state variables, and asymmetric oligopolistic firms in the estimation. The results show that the OS network size has a positive and significant impact on consumer utility. I then study two counterfactual cases in which I eliminate the OS network effect and the carriers' pricing strategy, respectively. I find that, without the OS network effect, the smartphone penetration rate would decrease by 54.7% and the largest OS share difference decrease by 31.7% by May 2013. Without the carriers' pricing strategy, the penetration rate would decrease by 29.1% and the OS market share difference decrease by 11.2%.Chapter 2"The Operating System Network Effect and Consumers' Dynamic Demand of Smartphones with Two-Year Contracts."This paper studies consumers' dynamic demand of smartphones on two-year wireless contracts. Individuals' demand decisions are affected by the improving quality and changing prices of smartphones, and the OS network effect, and their current smartphone contract status. Consumers need to pay high early termination fees if they end active contracts. The dynamic demand model in this paper incorporates the evolving choice set, prices, endogenous OS network sizes, and the termination policies in the smartphone industry. The preliminary results find that the OS network effect is large and significant. In addition, compared with dynamic model results, a static demand model tends to underestimate the OS network effect and overestimate price coefficient.Chapter 3"Store Brands and Retail Grocery Competition in Breakfast Cereals."This paper empirically analyzes the impacts of store brands on grocery retailers and consumers in the market for breakfast cereals. On the supply side, store brands help a retailer to avoid direct competition with other retailers and change the set of retailer's products. On the demand side, introducing store brands changes the national brands prices and consumers' choice set. We analyze the effects via demand estimation for a single grocery store chain Dominick's at Chicago in 1997 and counterfactual exercises. The estimation results show that consumers' unobserved utility of buying at a competing retailer is higher for consumers that value national brands, and is lower for ones that value Dominick's store brands. This is consistent with the claim that store brands help a retailer to avoid competition. The counterfactual calculations show that the profit loss from removing store brands is higher if the retailer has more competitors, with a median loss of 4.33% of profits from cereals. Existence of store brands increases national brands prices and consumer welfare increases slightly when store brands are removed.