Copyright enforcement in China has heightened competition among music streaming services for exclusive licenses. The market is now dominated by one company with the largest market share and streaming the most exclusive musical works. In this paper, I study whether exclusivity takes place as a mechanism leading to market concentration. My paper addresses important policy issues in intellectual property protection by focusing on its effect on market competition. I first use theoretical analysis and empirical facts to show that the competition is driven by the existence of switching costs for consumers in choosing among services. Exclusivity attracts users, benefiting the service in the future when the switching cost can be exploited as a lock-in device. I then estimate a dynamic structural model with switching costs using aggregate data from China's music streaming market over 2014-2017.  Finally, I simulate market outcomes under two alternative policies, a compulsory licensing provision and a mandatory data portability policy. The policy simulation shows that a compulsory licensing that enforces non-exclusive distribution would increase market concentration. In contrast, mandatory data portability that reduces switching costs would reduce market concentration by bringing more users to smaller services. 

The efficiency of resource allocation is often analyzed in static frameworks with a focus on the cross-sectional heterogeneity in the willingness to pay among users. When the resource is durable in nature, the temporal heterogeneity could be important in assessing the efficiency properties of different allocation mechanisms. This paper uses a dynamic model to empirically quantify the efficiency outcome of using lotteries to allocate scarce resources among forwardlooking consumers. In the context of the lottery policy for vehicle licenses in Beijing, our analysis shows that lotteries significantly affect intertemporal decisions in that households participate in lotteries at least four years earlier on average than they would be in a counterfactual environment of no quantity constraint. The welfare loss due to temporal heterogeneity and resulting changes in participation decisions accounts for over half of the total welfare loss from the lottery policy. The analysis highlights the importance of taking dynamic efficiency into account in designing resource allocation mechanisms.

During the great recession, many countries have adopted stimulus programs designed to achieve two goals: to stimulate economic activity in lagging durable goods sectors, and to protect or even enhance environmental quality. The environmental benefits are often viewed and much advocated as co-benefits of economic stimulus. This paper investigates the potential tradeoff between the stimulus and environmental objectives in the context of the popular U.S. Cash-for-Clunkers (CFC) program by developing and estimating a dynamic discrete choice model of vehicle ownership. Results from the counterfactual analysis show that design elements to achieve environmental benefits could significantly limit the program impact on demand stimulus: the cost of demand stimulus after netting out environmental benefits under the program could be 25% higher in terms of vehicle sales and 24%

higher in terms of consumer spending than that from alternative policy designs without explicitly aiming at the environmental objective. Our findings serve as a cautionary tale for similar green stimulus proposals to address the current economic crisis from the coronavirus pandemic.