The article discusses how social scientists can figure out cause and effect relationships using methods from microeconomics. It talks about the challenges of bias and reverse causality in experiments, and how different statistical methods can help draw conclusions even without perfect experiments. The researchers explain tools like difference-in-differences and regression discontinuity to study real-world situations. They also mention important things to consider like weighting and external validity. The article provides Stata code and checklists to help researchers apply these methods effectively.