Competition in the Digital Advertising: Russia and Global Trends

The largest digital platforms’ share is approaching 80% in 2023 in advertising sector including search, video, social media and other markets. Digital advertising is displacing traditional advertising. Digital platforms have network effects, special pricing, access to user data and algorithms for processing this data, allowing them not only to retain users, but also to more accurately classify them in order to offer targeted advertising. Research shows that the better a digital platform identifies user preferences, the higher the price it will offer. The literature shows that there is no generally accepted approach to determining prices in the digital advertising market, since it is carried out every second in online bidding (based on the header bidding system). Google plays a big role in the pricing process, as it owns the advertising exchange. If we don't understand what determines the price of digital advertising, we can't understand whether it is monopoly high. In this graduate work, I look at the CPM advertising price for Google Display, YouTube and Facebook* (part of Meta, banned in Russia as an extremist organization) and the factors that influence it. CPM is the cost per thousand views of an advertisement by users. For Russia, this analysis is of great interest. Russia's potential in the field of digital advertising is one of the highest in the world. At the same time, starting in 2022, radical changes are taking place in the Russian digital advertising market: the prohibition of some active participants in digital advertising (Meta*, Tik Tok) and the withdrawal of others from the market (Google, YouTube) is accompanied by a redistribution of digital advertising revenues in favor of domestic ones providers - Yandex, Telegram, VK and marketplaces. The proposed hypotheses are divided into groups according to the influence of user demand factors, supply factors, targeting accuracy factors (through conversion to purchase, traffic), the spread of the Internet and e-commerce, and the price of digital advertising. The empirical part of the work presents different models of panel analysis: for countries, for digital platforms Using price data from digital platforms Google Display, YouTube and Facebook*, and for a combination of country markets and digital platforms. To preserve time-invariant variables, the Hausman-Taylor model was used, and a two-level panel data model was proposed to deal with endogeneity. Hypotheses about the positive influence of targeting accuracy factors on the price of digital advertising were confirmed in different specifications.