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We are happy to announce good news for MA and PhD applicants who missed the March deadline. We are opening the 2nd round of admissions with a new deadline August 15.

Entry requirements are:
- BA or MA degree or equivalent
- Proficiency in spoken and written English
- Solid background in mathematics
- Previous education in economics is recommended

Your online application must content following documents:
- Curriculum vitae
- Statement of motivation
- Copies of your diplomas and transcripts
- Proof of English proficiency level
- Contact details for two (or max. three) referees

For more information please see sections: How to apply to MAER or How to apply to PhD
In case of any question, please do not hesitate to contact us at This email address is being protected from spambots. You need JavaScript enabled to view it. or This email address is being protected from spambots. You need JavaScript enabled to view it.
or see the FAQ sections for MAER or Phd

We would like to invite you to a one-off health econ seminar by Dr. Michal Horný from Emory University, USA. The seminar is organised within the framework of the Platform for Biomedical and Economic Research "IBER", which consists of the IOCB Prague, ECON MUNI and EI.

For online participation, you can use the following link and passcode:
https://call.lifesizecloud.com/20981341
Passcode: 5171

Abstract: Patients’ ability to understand and reliably anticipate the cost of care is critical for making informed decisions regarding provider and treatment alternatives and for household financial planning. Despite recent policies aimed at improving the discoverability of health care prices, meaningful information on the total cost of care is difficult to obtain for patients in the United States before receiving care. One of the key factors is the difficulty of predicting which services will comprise an episode of care. Consequently, pre-case cost estimates are often incomplete and unreliable. This is a fundamental problem of existing price transparency initiatives, which disclose prices to patients at the service level.

In this paper, I use childbirth as an example of a common, expensive, and “shoppable” health-related episode and quantify the financial risk for patients stemming from the ex-ante uncertainty in treatment intensity. Using administrative data from employer-sponsored insurance plans, I estimate the cost of childbirth episodes as a function of the realized treatment intensity and then estimate the financial risk as the cost variation that is not explained by patient choice or preexisting condition. Subsequently, I quantify the welfare gain for patients if their cost share were derived prospectively based on the expected treatment intensity conditional on their choices and preexisting conditions instead of retrospectively based on the realized treatment intensity.

I find that patients seeking childbirth services face substantial financial risk stemming from the unpredictable treatment intensity due to complications and other factors that are beyond patients’ control. This risk and consequent unexpected burden for some patients cannot be addressed by service-level price transparency. Novel cost-sharing mechanisms such as episode-based cost-sharing would protect patients from financial risk and improve the reliability of price signals in health care.

Prof. Ines Moreno de Barreda

University of Oxford, United Kingdom

Authors: Ines Moreno de Barreda, Evgenii Safonov

Abstract: An agent with a privately known continuous type applies for approval. While the agent always prefers approval over rejection, approving an agent with low type has social costs. The agent sends a report about her type that she can inflate by engaging in signaling costs that have the single-crossing property. We study approval mechanisms without transfers that maximize a social welfare function that takes into consideration both the approval decision and the signaling costs of the agent. We show that threshold approval rules, which are widespread in society, are never socially optimal. By introducing some randomness in the rule, we can reduce the signaling costs without substantially changing the screening of the rule. If we further assume that the marginal cost is strictly log-supermodular, an assumption satisfied by the quadratic-loss function, we show that the optimal approval mechanism induces an approval probability that is continuous in the agent's type. We provide necessary first-order conditions for the optimal rule, and illustrate them with an analysis of the case of quadratic-loss function and uniform distribution of the agents' types.