Digital advertising has seen dramatic growth over the last decade. Total digital ad spending in the US has increased 6 times between 2010 and 2020, from $26 billion to $152 billion(eMarketer). This impressive development has in turn sparked a huge stream of literature studying all the different aspects of advertising in the digital media. My dissertation contributes to this literature via two essays. In the first essay, I consider a very important topic of ad blocking, that in the recent years has become a significant threat to advertising supported content. With a specific focus on consumer and total welfare, I show the detrimental role of the adblockers’ current revenue model in decreasing content quality, consumer surplus and total welfare. In the second essay, I study demand learning in digital advertising markets, where firms learn over time how their advertising campaigns impact consumer demand by using their advertising campaign outcomes in earlier periods. By developing an analytic model, I demonstrate in several scenarios, such as monopoly and competition, that learning has an ambiguous effect on the key market parameters and, in particular, on the equilibrium advertising and quantities.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-k5bf-4g85 |
| Date | January 2021 |
| Creators | Gritckevich, Aleksandr |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
Page generated in 0.0024 seconds