MRSS Talk by Pedro Gardete, NOVA School of Business and Economics (PT)

As part of his visit to WU Vienna, Professor Pedro Gardete also gave a research seminar, presenting his work Subscription Pricing and Demand Alignment, co-authored with Daniela Schmitt (NOVA SBE) and Florian Stahl (University of Mannheim).

The research starts from a question that sounds simple but turns out to be surprisingly subtle: does the price of a subscription shape only who subscribes, or also how much they use the service? Standard economic intuition says that people who pay less value the product less and should consume less. Using data from a European online news publisher, the authors show the opposite: subscribers who joined during a price promotion read considerably more than those who paid the regular price. The key lies in demand alignment, the correlation between consumers’ willingness to pay and their consumption intensity. The authors develop a model that recovers this correlation from the data and use it to study how firms should design their pricing.

Professor Gardete highlighted several key conclusions:

• Subscription demand depends only on the marginal distribution of consumer surplus, but optimal pricing, profits, and welfare depend critically on demand alignment.

• At the estimated level of alignment, charging a single flat fee is optimal. This may help explain why usage-based price discrimination is relatively rare across industries.

• Richer pricing menus only pay off once the correlation becomes positive, and even then only modestly, because the seller has limited content available.

• When comparing markets, more favorable price schedules do not necessarily mean higher welfare, since prices reflect the composition of demand the firm faces in the first place.

Professor Gardete has a real knack for making even complex topics accessible, always with a smile. His clear and engaging presentation sparked a lively discussion and gave participants plenty to think about, both on subscription business models and on how careful modeling can overturn seemingly obvious intuitions.