UC Berkeley

The dissertation has two chapters. In the first chapter, called “Optimal Policies for Differentiated Green Products: Characteristics and Usage of Electric Vehicles”, I study the issue of policy design for electric vehicles. When designing policies for electric vehicles (EVs) policymakers need to decide how to allocate policy support among EVs with different characteristics, since different EVs are likely to have differences in attractiveness to consumers and usage patterns and, hence, differences in environmental impact. In this paper, I build and estimate a structural model of the U.S. auto market that is able to predict market shares and usage patterns of electric and traditional vehicles with different characteristics under various market conditions and is able to assess the effects of policies differentiating on characteristics of EVs. On the demand side, I introduce the concept of consumer inconvenience costs of charging, which depend on EV battery range, charging infrastructure development level, consumer's driving needs, and other individual-specific factors. On the supply side, I model firm choice of prices and battery ranges. The estimation results show that the inconvenience costs have a dramatic effect on consumer purchase decisions and usage patterns of EVs, and, hence, their environmental impact. Also, the results indicate that firms are more likely to adjust battery ranges when policy support depends on battery range. I use the model estimates to evaluate the effects of two major U.S. policies for EVs, the federal subsidy and California's Zero Emission Vehicle regulation, on the environment, consumer surplus, firm profits, and social welfare. I also experiment with alternative structures of the federal subsidy that differentiate on type and battery range of EVs. I find that more efficient structures can improve the environmental effect of the subsidy by 4.6% and the welfare effect by 1.6%. Interestingly, the more efficient structures result in fewer EVs sold, but in more electric miles traveled and more gasoline miles replaced.In the second chapter, called “Do Big Businesses Influence Media? The Case of Amazon.com and The Washington Post.”, I study whether media outlets bias their coverage of the news about their owners or companies the owners have vested interests in. To shed some light on this question, I look at how the acquisition of the Washington Post, a major U.S. daily newspaper, by Jeff Bezos, the founder and CEO of Amazon.com, affected the coverage of the news about Bezos and Amazon.com. Using data on news stories in several major newspapers, I document that the acquisition resulted in an increase in the number of mentions of Bezos, Amazon, or Amazon’s products in the Washington Post, relative to other newspapers and news stories about other big tech companies. From a simple sentiment analysis, however, I found no evidence of change in the sentiment of the stories. I discuss potential mechanisms that can explain the results, including a conflict of interest, a shift in preferences of the readership, improved access of the Washington Post to information about Bezos and Amazon, and a shift in the beliefs of the newspaper’s editors and journalists about the importance of news about Amazon and Bezos.