Pre-Conference

The aim of stated preference methods is to reveal (through cost-benefit analyses (CBA)) whether the potential change in utility resulting from a change in the level of provision of a good is positive. The welfare implications are typically expressed in terms of the monetary amount which needs to be taken from or given to the agent to keep the agents’ overall utility constant. In contrast to cost-effectiveness analysis CBA is thought to have the advantage that it is not a priori constrained as to what elements of utility it measures. It is, however, important to be aware that the design of the stated preference question determines what elements of utility are included in the valuation task.

The payment vehicle is a key instrument for measuring the utility associated with health care services in stated preference methods. But are we sufficiently aware of what precisely we are measuring, what we want to measure, and the potential biases in the way we frame our question? Choice of payment vehicle, and whether one applies an ex ante or ex post valuation perspective will have implications for which sources of value are captured in our willingness-to-pay estimate: use value, option value and/or altruism? And what are the implications of respondents being pure as opposed to paternalistic altruists? Or impure altruists? Other points for discussion are issues associated with health state dependent utility and income constraints.

The workshop illustrates potential pitfalls and challenges associated with framing the stated preference question and points towards scope for future research. The half-day workshop is for researchers interested in valuing health care interventions by way of willingness-to-pay. The workshop will involve lectures, ongoing dialogue and small group tasks.

The session aims to offer a comprehensive overview of the political economy of health and healthcare, spanning current and future research in this domain. Structured into three hour-long sessions, it will delve into various aspects of this field.

The initial session will serve as an introduction to the political economy of healthcare, exploring the impact of democracy on health, the emergence of the concept of the "patient-citizen," the role of constitutional safeguards for the right to health, and the role of political regimes in shaping health outcomes.

The subsequent segment will examine the effect of multilevel governance of healthcare decisions, with a particular focus on the decentralization of European healthcare systems, and the dynamics between public and private healthcare provision across different jurisdictions. Drawing on insights from the COVID-19 pandemic, this part will study the effect of decentralization and interjurisdictional spillovers in health care, laying the groundwork for a potential European Health Union.

Lastly, the third session will elucidate the fundamental principles governing the political demand and supply of healthcare. It will explore the role of ideology, interest groups, and cabinet composition, including the influence of medical professionals and women in decision-making processes. Additionally, it will present recent research on the ideological underpinnings shaping healthcare demand, shedding light on areas where our understanding remains limited.

Choice modelling is widely used in transport, marketing, environmental and health economics for understanding choice behaviour and forecasting demand for products and services. In health, choice modelling is used – among other applications – to measure patient preferences validly and reliably as well as accurately predict choice behaviour of patients. As such, it can help to tailor care to patients’ needs, and prevent (i) non-adherence to treatments (ii) waste in healthcare, (iii) poor policy decisions, (iv) trial-and-error policy implementations, and (v) supply and demand imbalance.

In this half-day workshop ‘Choice Modelling in Health’, participants will familiarize themselves with the practical steps for conducting a stated preference study (including a Discrete Choice Experiment) and modelling choice data. The theoretical underpinnings will be presented in an interactive environment.

Participants will be introduced to the R programming language and Apollo, commonly used for estimating choice models in academia and industry. Participants will learn the step-by-step modelling process for estimating the most commonly applied choice models in health: the Multinomial Logit (MNL), the Latent Class (LC) and Mixed Logit (MXL) models; familiarize themselves with preference heterogeneity, model output and model comparison; conduct post-estimation procedures to transform model outcomes to useful insights that suit the needs of stakeholders in health (e.g. Marginal Rates of Substitution (including Willingness-to-Pay or Maximum Acceptable Risk), relative attribute importance, choice probabilities, and market shares). The half-day workshop is at a beginner’s level and contains three lectures (90mins in total), two practicums (75mins in total), and a short 15-minute break.

Please note that for this Pre-Conference Workshop a notebook is required.

This interactive workshop focuses on the principles and practical application of data visualization and how statistical graphics can enhance applied econometric analysis and policy evaluation in health economics. Methods for policy evaluation include regression methods for panel data such as differences-in-differences, synthetic controls and their extensions. The workshop extends the data visualization approach to illuminate econometric analysis of health care cost regressions and distributional analysis of health outcomes. It encourages a critical approach to the appraisal of visualizations. The workshop also introduces some key concepts and practices of "machine learning" (ML) and reviews the rapidly growing literature that combines applied econometrics with machine learning for better predictions and estimation of treatment effects in health economics. Machine learning lies at the intersection of computer science and statistics, using learning-based algorithms to make predictions from data. The workshop reviews some important developments in econometric policy evaluation. There is a particular emphasis on methods for aggregate panel data ("comparative case studies"), including extensions of differences-in-differences and synthetic control methods. Practical examples will show how these methods can be applied and the workshop outlines a grammar of graphics in Stata.

This course aims to provide participants with an overview of behavioral experiments in health economics and thereby to convey a solid understanding of the state-of-the-art experimental methodology as well as practical insights to conduct own experiments.

Topics covered, among others, are experiments on provider behavior, incentives, and elicitation preferences in health. The course will present different types of experiments (lab, online, field) and give examples of their use to address health-economics issues complementing theory and empirical work. During the practical phase of the course, participants will have the opportunity to engage in discussions and present their own experimental design ideas.

The intended learning objective is that by the end of the course, participants will know how to apply experimental methods in their own research.