Enhanced DiD Lab: Pre-trends Testing
Explore Difference-in-Differences with multiple time periods. Test the crucial parallel trends assumption by examining pre-treatment trends and see how violations affect your causal estimates.
Controls
Violation of parallel trends in pre-periods
Quick Scenarios
DiD with Pre-trends Analysis
Results & Diagnostics
Group Means
DiD Calculation
Understanding Pre-trends
Why Pre-trends Matter
DiD assumes treatment and control groups would follow parallel trends without intervention. Pre-treatment periods let us test this assumption.
What to Look For
Before policy implementation, the two groups should have similar slopes. Differential pre-trends suggest the assumption is violated.
Try This: Set differential pre-trend to 2.0 and see how it biases your DiD estimate even when the true treatment effect is 0!
Stata Implementation
Master More Causal Inference Methods
Now that you understand DiD and pre-trends testing, explore other quasi-experimental methods for identifying causal effects when randomization is not possible.