Part 2 – The claim and its estimand
Part 2 is the conceptual middle of the day. It reads the paper in full, then argues that analysts who look as though they disagree are often answering different questions, and it gives you the vocabulary for saying which question you are answering.
| Work through | What you do | Timing |
|---|---|---|
| Slides, Part 2 | The paper in full: the four framing scales, the model that the original author (OA) fitted, Model 1 and Model 2, which put the robustness question inside the paper, the two failed attempts to reproduce the paper and the replication on new data whose estimate had the opposite sign, and the five questions that the Multi100 analysts asked in the free phase, when each chose their own analysis. | 20 minutes |
| Slides, the estimands run | Two studies set beside our five: the red-card estimates again as a single row, four different estimands drawn out of one football question, and the spread that collapses once the estimand is fixed. Then Lundberg’s three steps from a theoretical quantity to an empirical one. | 25 minutes |
| Slides, the causal-graph crash course | Confounders, mediators and colliders; open and closed paths; total against direct effects; selection and feedback. Then the return to our own claim, where everyone writes a one-sentence estimand, holds it, and sends it together. | 25 minutes |
R/dag_starter.R in the workspace, or Browser lab Task 2, with Causal graphs as the slower companion |
An optional R tutorial runs first if the class wants it. Then look at the panel and find the countries that move sharply around 2009; write the estimand in words; take the # off the arrows you are willing to defend, re-run adjustmentSets(), and write two sentences on what two-way fixed effects adjust for and what they cannot fix. |
18 minutes |
By the end of the part you have the estimand behind the claim written in one sentence, a graph that includes only the arrows you are willing to defend, and the adjustment set that follows from it.