Working papers

This figure shows the percentage of seller types that is correctly predicted. Obtained after calibrating the model to our data.

Learning from Online Ratings

joint with Xiang Hui and Konrad O. Stahl


February 2024

also available as C.E.P.R. Discussion Paper 17006

the earlier February 2022 version with a different title is also available as CRC TR 224 Discussion Paper No. 267


Online ratings play an important role in many markets. However, how fast they can reveal seller types remains unclear. We propose a new model of rating behavior where learning about the seller type influences the rating decision. We calibrate the model to eBay data and find that ratings can be very informative. After 25 transactions, the likelihood of correctly predicting the seller type is above 95 percent.

This figure shows that cost-sharing policies that lead to higher premiums tentatively lead to lower welfare of predictable sick individuals.

Patient cost-sharing and redistribution in health insurance

joint with Martin Salm and Suraj Upadhyay


January 2024

also available as C.E.P.R. Discussion Paper 18395 and IZA Discussion Paper No. 16778


Health insurance premiums often do not reflect individual health risks, implying redistribution from individuals with low health risks to individuals with high health risks. This paper studies whether more cost-sharing leads to less redistribution and to lower welfare of high-risk individuals. This could be the case because more cost-sharing increases out-of-pocket payments especially for high-risk individuals. We estimate a structural model of healthcare consumption using administrative data from a Dutch health insurer. We use the model to simulate the effects of a host of counterfactual policies. The policy that was in place was a 350 euro deductible. Our counterfactual experiments show that redistribution would decrease when the deductible would increase. Nonetheless, high-risk individuals can benefit from higher levels of cost-sharing. The reason is that this leads to lower premiums because both high-risk and low-risk individuals strongly react to the financial incentives cost-sharing provides.


This figure shows the dependence of search result quality on the amount of data that a search engine uses to produce search results. There are 5 lines, for 5 levels of popularity of the query.

How important are user-generated data for search result quality?

joint with Madina Kurmangaliyeva, Jens Prüfer, and Patricia Prüfer


October 2023

the earlier March 2023 version is also available as C.E.P.R. Discussion Paper 17934

the earlier September 2022 version appeared as TILEC Discussion Paper No. 2022-16, CCP Working Paper No. 22-07, and was discussed in the CCP Policy Brief


Do search engines produce better results because their algorithm is better, or because they can access more data from past searches? We document that the algorithm of a small search engine can produce non-personalized results that are of similar quality to the dominant firm’s (Google) if it has enough data. Overall differences in the quality of search results are explained by searches for rare queries. This is confirmed by results from an experiment, in which we keep the search engine algorithm fixed and only vary the amount of data it uses as input.

This figure shows the evolution of the price patients paid for a dermatological procedure. The treatment group had transparent prices from week 31 onward, while the control group did not.

Increasing price transparency in the Dutch health care market does not affect provider choice

joint with Maciej Husiatyński and Misja Mikkers


March 2021

also available as C.E.P.R. Discussion Paper 15981


Price transparency is often viewed as an effective way to encourage price shopping and thereby lower health care expenditure. Using individual claims data for 6 frequent, non-emergency dermatological procedures, we estimate the short-run effect of unexpected publication of prices by a major Dutch health insurer on spending and provider choice. Visits to the price transparency website surged, but spending, the likelihood to visit a new provider, distance traveled, and type of provider visited remained unaffected.

Price Competition in Two-Sided Markets with Heterogeneous Consumers and Network Effects

joint with Lapo Filistrucchi


September 2013

NET Institute Working Paper #13-20 


We model a two-sided market with heterogeneous customers and two heterogeneous network effects. In our model, customers on each market side care differently about both the number and the type of customers on the other side. Examples of two-sided markets are online platforms or daily newspapers. In the latter case, for instance, readership demand depends on the amount and the type of advertisements. Also, advertising demand depends on the number of readers and the distribution of readers across demographic groups. There are feedback loops because advertising demand depends on the numbers of readers, which again depends on the amount of advertising, and so on. Due to the difficulty in dealing with such feedback loops when publishers set prices on both sides of the market, most of the literature has avoided models with Bertrand competition on both sides or has resorted to simplifying assumptions such as linear demands or the presence of only one network effect. We address this issue by first presenting intuitive sufficient conditions for demand on each side to be unique given prices on both sides. We then derive sufficient conditions for the existence and uniqueness of an equilibrium in prices. For merger analysis, or any other policy simulation in the context of competition policy, it is important that equilibria exist and are unique. Otherwise, one cannot predict prices or welfare effects after a merger or a policy change. The conditions are related to the own- and cross-price effects, as well as the strength of the own and cross network effects. We show that most functional forms used in empirical work, such as logit type demand functions, tend to satisfy these conditions for realistic values of the respective parameters. Finally, using data on the Dutch daily newspaper industry, we estimate a flexible model of demand which satisfies the above conditions and evaluate the effects of a hypothetical merger and study the effects of a shrinking market for offline newspapers.