This doctoral thesis and its associated papers address empirical research questions in the fields of competition policy and health economics. In all five papers, empirical microeconomic tools are applied to identify and measure causal links. Mostly, (quasi) natural experiments are employed to estimate the impact of policy interventions on market outcomes. The connection between the five papers in this thesis is that causal inference methods are used to analyze economic policy issues. Causal inference is the process of uncovering causal effects by estimating the impact of events and choices on a given outcome of interest (see Cunningham (2021)). In the papers of this thesis, observational data is used to answer the individual research questions. However, correlations in this type of data are mostly not reflecting causal relationships because the variables are based on choices of individuals which create spurious correlations with other things (see Huntington-Klein (2021)). Hence, causal inference methods are needed to identify causal links based on certain assumptions.
