Lecture 26 Causal Inference Midterm Review
Nick Huntington-Klein
March 28, 2019
Causal Inference Midterm
- Similar format to the homeworks we’ve been having
- At least one question evaluating a research question and drawing a dagitty graph
- At least one question identifying the right causal inference method to use
- At least one question about the feature(s) of the methods
- At least one question carrying out a method in R
Causal Inference Midterm
- Covers everything up to IV (obviously, a focus on things since the Programming Midterm, but there is a little programming)
- No internet (except dagitty) or slides available this time
- One 3x5 index card, front and back
- You’ll have the whole class period so don’t be late!
Causal Diagrams
- Consider all the variables that are likely to be important in the data generating process (this includes variables you can’t observe)
- For simplicity, combine them together or prune the ones least likely to be important
- Consider which variables are likely to affect which other variables and draw arrows from one to the other
- (Bonus: Test some implications of the model to see if you have the right one)
Causal Diagrams
Identifying X -> Y
by closing back doors:
- Find all the paths from
X
to Y
on the diagram
- Determine which are “front doors” (start with
X ->
) and which are “back doors” (start with X <-
)
- Determine which are already closed by colliders (
X -> C <- Y
)
- Then, identify the effect by finding which variables you need to control for to close all back doors (careful - don’t close the front doors, or open back up paths with colliders!)
Causal Diagrams
- Let’s draw (and justify) a diagram to get the effect of Building Code Restrictions
BCR
, which prevent housing from being built, on Rent
- Consider perhaps: the
Sup
ply of housing built, characteristics of the loc
ation that lead to BCR
s being passed, Dem
and for housing in the area, the overall economy…
Causal Diagrams Answer
One answer, with non-BCR Laws
, Labor
market, econ
omy: