Difference in Differences (DiD) is a statistical technique used to estimate the causal effect of a treatment or policy intervention using panel data. It compares the average changes over time between treated and untreated groups.
Propensity Score Matching is a statistical method used to estimate the causal effect of a treatment or policy intervention in observational data by comparing the outcomes of treated and untreated subjects who are otherwise similar in their observed characteristics.
Regression Discontinuity Design (RDD) is a statistical method used to estimate the causal effect of an intervention by assigning treatment based on a continuous assignment variable threshold.
