#DifferenceinDifferences
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liser.lu
📽️ Watch a 12 hour course by Prof. @cdechaisemartin.bsky.social on #DifferenceInDifferences (DiD), hosted at LISER.

💡 The course begins w/ a review of fundamental concepts & progresses to advanced techniques, emphasizing the latest innovations in DiD revolution.

🔗 www.youtube.com/playlist?lis...
May 8, 2025 at 9:36 AM
causalhuber.bsky.social
🔥 #EconSky Check out my new paper on #DifferenceInDifferences, exploring the testability of the common trend assumption in panel data without requiring multiple pre-treatment periods for placebo tests: arxiv.org/abs/2404.16961
On the testability of common trends in panel data without placebo periods
We demonstrate and discuss the testability of the common trend assumption imposed in Difference-in-Differences (DiD) estimation in panel data when not relying on multiple pre-treatment periods for...
arxiv.org
April 29, 2024 at 6:39 AM
nmoreaukastler.bsky.social
… Stata command coming soon ! 👩‍💻

9/9

#EconBluesky #Econometrics #Differenceindifferences
May 7, 2025 at 8:26 AM
causalhuber.bsky.social
#EconSky: Our working paper on #MachineLearning for staggered #DifferenceInDifferences is out! Our method explores effect heterogeneity under staggered treatment adoption and is applied to assess the effect of Brazil's Family Health Program on infant mortality: arxiv.org/abs/2310.11962
Machine Learning for Staggered Difference-in-Differences and...
We combine two recently proposed nonparametric difference-in-differences methods, extending them to enable the examination of treatment effect heterogeneity in the staggered adoption setting using...
arxiv.org
October 26, 2023 at 8:10 AM
causalhuber.bsky.social
😀 New paper alert! Check out our #DifferenceInDifferences method for time-varying continuous treatments based on double #MachineLearning and kernel methods - joint work with Michel Haddad and Lucas Zhang: arxiv.org/abs/2410.21105 #CausalAnalysis
Difference-in-Differences with Time-varying Continuous Treatments using Double/Debiased Machine Learning
We propose a difference-in-differences (DiD) method for a time-varying continuous treatment and multiple time periods. Our framework assesses the average treatment effect on the treated (ATET) when co...
arxiv.org
October 31, 2024 at 3:39 PM
dliebl.com
📄 Paper: arxiv.org/abs/2512.06804
📦 R package: ccfang2.github.io/fdid/

Joint work with my PhD student Chencheng Fang — he did a fantastic job.
▶️ ccfang2.github.io

#CausalInference #DifferenceInDifferences #Econometrics #EventStudy #Statistics #RStats #AcademicResearch
Making Event Study Plots Honest: A Functional Data Approach to Causal Inference
Event study plots are the centerpiece of Difference-in-Differences (DiD) analysis, but current plotting methods cannot provide honest causal inference when the parallel trends and/or no-anticipation a...
arxiv.org
January 21, 2026 at 9:29 AM
stathorizons.bsky.social
Join Gonzalo Vazquez-Bare on June 23-26 for a course on the latest developments in #DifferenceinDifferences. You will learn to apply classical and novel methods for estimating treatment effects and to evaluate the assumptions behind them.
Difference in Differences | Online Training | Statistical Horizons
Live online course on difference in differences. Learn to use DiD models for causal inference, treatment effects, and policy evaluation.
statisticalhorizons.com
May 15, 2026 at 1:29 PM
arxivlens.bsky.social
Bias-Variance Tradeoff of Matching Prior to Difference-in-Differences
When Parallel Trends is Violated
Dae Woong Ham, Mingxuan Ge
Paper
Details
#BiasVarianceTradeoff #DifferenceInDifferences #ParallelTrendsViolation
October 26, 2025 at 4:03 PM