Web Reference: Difference-in-Differences (DID) analysis is a statistic technique that analyzes data from a nonequivalence control group design and makes a casual inference about an independent variable (e.g., an event, treatment, or policy) on an outcome variable Differences-in-Differences regression (DID) is used to asses the causal effect of an event by comparing the set of units where the event happened (treatment group) in relation to units where the event did not happen (control group). Difference in differences requires data measured from a treatment group and a control group at two or more different time periods, specifically at least one time period before "treatment" and at least one time period after "treatment."
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