Course
Econometrics
What a regression coefficient identifies when the data were observed rather than assigned, and what would have to be true for it to be read as an effect.
Finishing this course means you have demonstrated the required skills with the level of support this course currently assesses.
- Modules
- 1
- Lessons
- 1
- Skills
- 1
- Starting here
- Assumes 2 prior topics
The route
Module 1: Identification
The three mechanisms that separate a coefficient from an effect, the formula that gives the size and direction of omitted-variable bias, why no diagnostic computed from the fit can detect it, and what an instrument would have to satisfy to repair it.
- The learner can identify the sources of endogeneity that make a least-squares coefficient differ from the causal effect, compute the direction and size of omitted-variable bias from the bias formula, explain why goodness of fit carries no information about that bias, and state what an instrumental variable would have to satisfy to repair it.
What finishing means
Finishing this course means you have demonstrated the required skills with the level of support this course currently assesses.
1 required skill. If you reach a lesson without the background it assumes, you are pointed at the prerequisite first, and returned here afterwards.
How progress is measured
Progress is inferred from evidence you produce, not from pages you have opened. Each required skill moves through states as evidence accumulates: met, practicing with help, performed unassisted, then performed again after a delay.
This course counts a skill as finished atguided. Where the system cannot admit evidence for a stronger claim — for instance when the only available scoring is your own judgment of your written answer — the skill stays at the state the evidence supports, and the reason is shown rather than hidden.