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The estimate is in the design
On stacking, discrete outcomes, matched inference, and data-driven controls
Mar 30
•
Beatriz Gietner
14
January 2026
The outcomes you measure and the assumptions holding them up
New papers on compositional shifts, coarsened outcomes, pre-trend testing and event-study identification
Jan 12
•
Beatriz Gietner
8
3
1
November 2025
On Finding Causes vs. Finding Levers
What are you actually trying to say?
Nov 18, 2025
•
Beatriz Gietner
19
6
5
Hidden Bias, Pie Charts and Spillovers
What to consider when reality has stopped cooperating
Nov 3, 2025
•
Beatriz Gietner
4
October 2025
Missing and Messy
A DiD horror story?
Oct 8, 2025
•
Beatriz Gietner
7
1
September 2025
Where Standard Assumptions Go To Die
Universal treatments without clean controls, continuous policies without untreated groups, reversible reforms over time and statistical inference with…
Sep 22, 2025
•
Beatriz Gietner
19
2
August 2025
Parallel Trends… Conditionally: Covariates, Violations, and More Robust DiD Methods
The devil in the ~DiD details~
Aug 11, 2025
•
Beatriz Gietner
9
1
DiD+: Handling Data Constraints, Timing Issues and TWFE Limitations
What to do when data can't be pooled, timing gets messy, and TWFE isn't enough
Aug 1, 2025
•
Beatriz Gietner
6
2
July 2025
Heterogeneity, Small Sample Inference, Anticipation, and Local Projections
On uniform confidence bands for conditional effects, a simple approach for small-N inference, refining the "no anticipation" assumption, and the LP-DiD…
Jul 22, 2025
•
Beatriz Gietner
8
1
June 2025
Efficient Estimation, Sequential Synthetic Control DiD, and the TWFE Debate
Some practical insights for a more precise and robust estimation.
Jun 27, 2025
•
Beatriz Gietner
16
2
All About Heterogenous Treatment Effects
The power of disaggregated causal effects.
Jun 20, 2025
•
Beatriz Gietner
18
3
In defense of Machine Learning in Economics
Why the common criticisms are outdated, and how new methods are making causal inference stronger.
Jun 10, 2025
•
Beatriz Gietner
34
3
9
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