Lesson 5
Types of economic data
Big question
Why does the structure of a dataset matter?
Lesson progress
Complete checkpoints as you learn
Learning objectives
- Explain types of economic data in plain language.
- Use cross-sectional data correctly in an interpretation.
- Connect the lesson idea to a formula, graph, Python result, or real example.
Simple explanation
Economic data can describe many people at one time, one unit over time, repeated cross sections, or the same units over time. The data type affects the questions we can answer and the methods we use.
Key terms
- Cross-sectional data
- Many units observed at one point in time.
- Time-series data
- One unit observed across many time periods.
- Pooled cross sections
- Cross-sectional samples from multiple time periods.
- Panel data
- The same units observed across multiple time periods.
Example
A survey of workers in 2026 is cross-sectional. Monthly inflation for Canada from 2000 to 2026 is time-series data.
| Type | Units | Time pattern |
|---|---|---|
| Cross-sectional | Many units | One period |
| Time-series | One unit | Many periods |
| Pooled cross sections | Many units | Several periods |
| Panel | Same units | Several periods |
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
Which data type follows the same units over time?
Key takeaway
The data structure shapes both the research design and the interpretation.