The Economics of Quality Investment in Mobile Telecommunications

Patrick Kainin Sun
This dissertation studies the U.S. mobile telecommunications industry, with a particular emphasis on the incentive to maintain antenna facilities, or base stations, to produce better signal quality. It combines insights from economic analysis to draw inferences from unique datasets for the state of Connecticut. Chapter 1 gives a broad overview of the industry and highlights the apparent importance of signal quality as a driver of demand. Publicly available information reveals that plan
more » ... phone selection, and pricing seem to be less determinant of overall quality relative to the quality of the call network. Reduced form evidence from proprietary data on demand and base station location data from Connecticut confirm that signal quality is important and that base stations are important to signal quality. Given the importance of base stations, Chapter 2 asks what are the competitive incentives to provide them and how would these incentive change in proposed mergers between two of the four largest firms in this industry. To answer this question, I use proprietary demand data and base station locations to estimate a structural model of supply and demand in this industry. I use a measure of land use regulation stringency from data on Connecticut zoning codes as instruments for the costliness of construction. Overall, I find base stations to have important competitive implications, as they represent a significant proportion of costs. Simulating mergers between AT & T and T-Mobile and Sprint and T-Mobile, I find the mergers induce increased differentiation between merging partners, a finding consistent with the previous literature. However, the natural efficiency of being able to use a single network instead of two can make the mergers welfare-improving. The results imply that merger reviews in industries with networks should investigate the scope of network integration as potentially important efficiency. Chapter 3 expands on the instrumental variable in Chapter 2 and explores how exactly [...]
doi:10.7916/d8gh9h4z fatcat:z6gadev54ne77kq3vdqsslqcli