Ninon Moreau-Kastler
@nmoreaukastler.bsky.social
Researcher @taxobservatory.bsky.social @pse.bsky.social. International Trade, Development and Public Econ. PhD @ENS_ParisSaclay and @ENSdeLyon. Member of @WEPSecon initiative.
https://ninonmoreaukastler.com
https://ninonmoreaukastler.com
Proposed counterfactual estimator to recover RoR:
1. Estimate FE on untreated units
2. Predict counterfactual outcomes for treated
3. Compute average effect in levels
4. Scale by average counterfactual outcome
Matches RoR interpretation; generalizes 2×2 PPML.
Event study simulation:
8/
1. Estimate FE on untreated units
2. Predict counterfactual outcomes for treated
3. Compute average effect in levels
4. Scale by average counterfactual outcome
Matches RoR interpretation; generalizes 2×2 PPML.
Event study simulation:
8/
May 7, 2025 at 8:21 AM
Proposed counterfactual estimator to recover RoR:
1. Estimate FE on untreated units
2. Predict counterfactual outcomes for treated
3. Compute average effect in levels
4. Scale by average counterfactual outcome
Matches RoR interpretation; generalizes 2×2 PPML.
Event study simulation:
8/
1. Estimate FE on untreated units
2. Predict counterfactual outcomes for treated
3. Compute average effect in levels
4. Scale by average counterfactual outcome
Matches RoR interpretation; generalizes 2×2 PPML.
Event study simulation:
8/
What happens with staggered treatment and heterogeneous treatment effect?
In a simple example (N=2, T=3), I show that TWFE PPML is biased (similarly to TWFE OLS). It "downscales" treatment effects, analog to the negative weights problem.
4/
In a simple example (N=2, T=3), I show that TWFE PPML is biased (similarly to TWFE OLS). It "downscales" treatment effects, analog to the negative weights problem.
4/
May 7, 2025 at 7:54 AM
What happens with staggered treatment and heterogeneous treatment effect?
In a simple example (N=2, T=3), I show that TWFE PPML is biased (similarly to TWFE OLS). It "downscales" treatment effects, analog to the negative weights problem.
4/
In a simple example (N=2, T=3), I show that TWFE PPML is biased (similarly to TWFE OLS). It "downscales" treatment effects, analog to the negative weights problem.
4/