Digital Economy Summer School

Course Overview
 
Most of the firms' revenues in digital markets come from online advertisements. For example, internet users are exposed to ads when they visit a website. These ads are consumer-specific, based on the information gathered by the platform through the usage of cookies (e.g., Google, Facebook). This is a lucrative business, and large: 86% of Google's revenue comes from ads, mostly allocated using auction mechanisms.

Auctions are also key in allocating spectrum, the main internet input. The deployment of the 5G for providing high-capacity internet services requires an electromagnetic spectrum. In 2021, among other countries, Australia, India, Brazil, and the UK will allocate spectrum using auctions. These auctions will generate big revenues for these countries and will determine the structure of the internet market.

In this course, we will provide an introduction to the economics of auctions in digital markets. We will discuss basic results in auction theory, explore their implications for the design of the 5G spectrum auctions, and we will explain how advertisers bid for the placement of their ads either as the result of consumer search (keywords) or as display ads. We will discuss how the auction formats used by platforms have evolved over time, and focus on the two more successful auction designs, the Generalized Second-Price Auction (used by Google) and the Vickrey-Clarke-Groves Auction (used by Facebook), as well as on more recent developments of this market, such as the diffusion of new intermediaries (namely, Digital Marketing Agencies), and their implications for both the auction platforms and for consumers. Finally, we will analyze the data market that feeds these digital auctions.
         
Course Outline

• Elements of Auction Theory
• The market for online advertisement: Evolution and Main Auction Formats
• The use of data in digital auctions
• Designing 5G spectrum auctions.

Course overview

Artificial Intelligence (AI) is indicated as the factor that will likely originate a new industrial revolution. It will certainly affect many sectors of our economies, probably sooner than expected, and with important trade-offs. This short course aims addressing some of the forces and consequences that AI is and will bring, in particular, to industrial organization and market interactions.

• How markets and competition will be affected by AI?
• What implications for consumers privacy?
• What will be the impact of AI powered recommendation systems?
• Will AI reduce biases and discrimination or rather increase them?

We will focus on some of the topics that will pose imminent and relevant challenges in this rapidly evolving area, for economic research and policy makers.  

About the instructor

Emilio Calvano (PhD, Toulouse School of Economics, 2008) is Associate Professor of Economics at the University of Bologna, associate faculty at the Toulouse School of Economics and research fellow of the Centre for Economic Policy Research in London (CEPR). He is an applied theoretical economist whose research mainly focuses on the theory of Industrial Organization.

He has published in top international peer-reviewed outlets such as Science Magazine, American Economic Review, Management Science, American Economic Journal: Microeconomics, Economic Journal and International Journal of Industrial Organization and is associate editor at the Journal of Industrial Economics.

His research interests include the economics of artificial intelligence, the economics of platforms, information economics and competition policy. His recent work studies the impact of AI powered algorithms (such as pricing software and recommender systems) on digital markets