Lesson 8
Pooled cross sections
Big question
What happens when we combine cross-sectional samples from different periods?
Lesson progress
Complete checkpoints as you learn
Learning objectives
- Explain pooled cross sections in plain language.
- Use pooled data correctly in an interpretation.
- Connect the lesson idea to a formula, graph, Python result, or real example.
Simple explanation
Pooled cross sections combine separate cross-sectional datasets collected at different times. The units do not need to be the same in each period.
Key terms
- Pooled data
- Data combined from multiple samples or periods.
- Repeated survey
- A survey run in multiple years with new respondents each time.
- Period indicator
- A variable that records the year or period of each observation.
- Policy comparison
- A common use case when policy changes between periods.
Example
A wage survey from 2022 and another wage survey from 2026 can be pooled to compare wage patterns before and after a policy change.
Checkpoint activity
Pause and explain this lesson's main idea in your own words before moving forward.
Try it yourself
Write one plain-English sentence explaining the main idea from this lesson.
Common mistakes
Check these before you move on.
A regression coefficient describes a pattern unless the assumptions or research design support a causal interpretation.
Quick quiz
In pooled cross sections, do the same people have to appear in every period?
Key takeaway
Pooled cross sections are useful when we want cross-sectional comparisons across time.