The field of quantitative research has transitioned from classical regression models to research designs emphasizing causal interpretation. The credibility revolution has enhanced reliability in empirical economics by prioritizing research design quality and employing more experimental and quasi-experimental methods. The module introduces a potential outcome model and direct acyclic graphs to analyse the causal effects of policies in natural experiments and randomized control trials. It further discusses in detail recent developments in difference-in-difference and synthetic control methods. Staggered policy implementation and heterogenous impact is discussed. Finally, synthetic difference in difference, combining strengths of both methods is presented. The presentation of these methods is accompanied by practical demonstrations in R. Staggered difference-in-differences is illustrated through examples showcasing the heterogeneous impacts of preferential trade agreements and sanctions on trade flows. Synthetic control is demonstrated by evaluating the impact of Brexit on UK trade with the EU.