Keynote speaker

This year's keynote speaker will be Prof. Libertad Gonzalez, Professor of Economics at Universitat Pompeu Fabra and the Barcelona School of Economics.

"How family policies affect child health and development"

In this talk, Prof. Libertad Gonzalez will summarize some of her recent research studying the effects of family policies on child outcomes. The policies include cash transfers (child benefits), parental leave policies, and subsidized early childcare. She will discuss impacts on short- and medium-term outcomes, including newborn and child health, early child development, school outcomes, and the incidence of child maltreatment. The results of Prof. Gonzalez's research show how sometimes policies do not achieve their explicit goals, while having unanticipated (both positive and negative) side effects. The talk will conclude that research can be helpful both in evaluating policies ex-post, and in identifying potential pathways that may lead to children's improved health and development in the future.

Pre-conference workshops

There will be two pre-conference workshops, taking place on August 28.

Workshop 1 - Causal Machine Learning

Facilitator: Prof. Martin Huber, University of Fribourg

Description: This course provides an introduction to causal machine learning with applications using the software “R”. Causal machine learning aims at assessing the causal effect of some intervention or treatment, like offering or not offering medical treatment, on an outcome of interest, like health. The assessment of a causal effect requires that groups receiving and not receiving the treatment are comparable in background characteristics which also affect their health outcome (e.g., pre-treatment health, education, etc.). Causal machine learning can be used to generate such comparable groups in a data-driven way by estimating two separate models for how the characteristics affect the treatment and the outcome. Such approaches also permit detecting subgroups for whom the treatment effect is particularly large as a function of their observed characteristics (effect heterogeneity analysis). This is useful for optimally targeting specific subgroups by the treatment (optimal policy learning). The course discusses the underlying assumptions, intuition, and usefulness of machine learning for causal analysis. It also introduces various causal machine learning algorithms, like double machine learning and optimal policy trees. Using the statistical software “R” and its interface “R Studio”, these methods are applied to various real-world data sets.

Objectives: 1) To understand the ideas and goals of machine learning for causal analysis; 2) To understand the intuition, advantages, and disadvantages of alternative methods ; 3) To be able to apply causal machine learning to real-world data using “R” and “R Studio.”

Prerequisites: Introductory statistics (probability theory, conditional means, linear regression), basic command of the statistical software “R” is desirable, but not strictly required.

Workshop 2 - Academia or Beyond: Choose Your Health Econ Destiny

Description: This pre-conference workshop will present various career opportunities after successfully completing a PhD in (Health) Economics.

The first part will focus on academic careers. Carine Franc (French National Institute of Health and Medical Research)  and Matt Sutton (University of Manchester) will talk about academic positions for PhD graduates. They will focus on the European job market, particularly in the UK and France, describing the different types of positions available and explaining the detailed application procedures, flyouts, and the necessary documents that need to be prepared. Additionally, they will share personal experiences and tips on how to stand out in a competitive job market. The format will be very interactive, with a strong emphasis on audience engagement, and questions are highly encouraged throughout the session.

Part two of the workshop will focus on career options for PhD graduates (health economics and related fields) beyond the typical academic career path. A panel discussion will feature the following individuals: Amanda Gisler, Head of Education, Health, and Social Security at Lucerne Statistics (LUSTAT) and a member of their executive board, manages cantonal statistics and oversees planning and data service agreements. Maria-Eleni Syleouni is a marketing manager in health economics at the Ypsomed Group, leveraging data-driven insights and RWE to benefit patients and stakeholders. Dominik Wettstein, a member of the Executive Committee of the HSK purchasing cooperative, handles national contracts and data analytics for 2.4 million insured persons under Helsana, Sanitas, and KPT.

This interactive panel discussion will be facilitated by Kathryn Dawson-Townsend (University of Lucerne) and will include insights for the audience regarding non-academic CVs and how to best position yourself and your PhD outside academia.

Social Event during the conference

The Social Event, combined with the Conference Dinner, takes place on August 29, 7pm.

Conference participants are invited to take part in the Social Event at the Glacier Garden Lucerne (Gletschergarten). The Conference Dinner is an ideal opportunity for participants to engage in informal dialogue in a relaxed setting at a prominent location in Lucerne. During the dinner, participants will have the opportunity to take part in a guided tour of the Glacier Garden.

The Social Event is sponsored by the Swiss Society of Health Economics sggö.

Directions to the Social Event

The address of the Glacier Garden Lucerne is Denkmalstrasse 4a, 6006 Lucerne. The Glacier Garden Lucerne can be reached on foot from the University in about 20 minutes. Bus no. 1 (direction Luzern, Maihof) runs from Lucerne train station to the "Löwenplatz" stop, from where it is a three-minute walk.