On this page, I compile publicly available resources for data preparation and analysis, writing and other grad school shenanigans. As a conscientious causal inference enthusiast, I comprehensively demonstrate the application of cutting-edge causal inference techniques based on my personal projects.

Teaching and Resources

Writing Tips

Coding Tips

Stata
Coming soon…
Python
Coming soon…
R
Coming soon…
GAMS
Coming soon…
Github
Coming soon…
LaTeX
Coming soon…

Causal inference

OLS
Coming soon…
RCT
Coming soon…
Difference-in-Differences (DiD) & event studies
- Classical DiD (Canonical 2x2 DiD)
  Coming soon…
- DiD with Multiple Time Periods (Pre and/or Post)
  Coming soon…
- Two-way Fixed Effects (TWFE)
  Coming soon…
- Event study DiD (Traditional Approach)
  Coming soon…
- Staggered DiD (Callaway & Sant’Anna Estimator, CSDiD)
  Coming soon…
- Sun & Abraham Estimator (SA)
  Coming soon…
- Imputation-based DiD
  Coming soon…
- Gardener Two-stage DiD (Clean controls)
  Coming soon…
- de Chaisermartin & D’Haultfoeuille Estimator(DID_M, DID_CSR)
  Coming soon…
- Stacked Regression /Pooled Estimators
  Coming soon…
- Local Projects DiD (LP-DiD)
  Coming soon…
- Synthetic DiD
  Coming soon…
- Triple-Difference (DDD/DiDiD)
  Coming soon…
- Fuzzy DiD
  Coming soon…
- Continuous Treatment DiD (Dose-Response DiD)
  Coming soon…
- Spatial DiD / DiD with spillovers
  Coming soon…
- Changes-in-Changes (CiC)
  Coming soon…
- Quantile DiD (QDiD)
  Coming soon…
- Matrix Completion DiD
  Coming soon…
- DiD with Reversible Treatments (Switchback or On-Off Designs)
  Coming soon…
- DiD with Instrumental Variables (IV-DiD /DiDIV)
  Coming soon…
- DiD for repeated Cross-Sections
  Coming soon…
- Repeated Cross-Sectional Synthetic DiD (RC-SDiD)
  Coming soon…
- DiD with Matching/reweighting (e.g. PSM-DiD, IPW-DiD)
  Coming soon…
- Doubly Robust DiD (DR-DiD)
  Coming soon…
- DiD with Anticipation Effects/Aschenfelter Dips
  Coming soon…
- Functional Difference-in-Difference (fDiD)
  Coming soon…
- Bayesian DiD Approaches
  Coming soon…
- Machine Learning-Enhanced DiD
  Coming soon…
- DiD Estimators When No Unit Remains Untreated
  Coming soon…
- DiD for Continuous Treatments and Instruments with Stayers
  Coming soon…
Synthetic Control Methods (SCM)
- Canonical Synthetic Control Method (SCM)
  Coming soon…
- Generalised Synthetic Control Method (GSC)
  Coming soon…
- Augmented Synthetic Control Method (ASCM)
  Coming soon…
Instrumental Variable (IV) Based Techniques
- Standard (two-stage Least squares) IV
  Coming soon…
- Endogenous Treatment Regressions (ETR)
  Coming soon…
- Endogenous Switching Regressions (ESR)
  Coming soon…
- Multinomial Endogenous Switching Regressions (MESR)
  Coming soon…
- Shift-share IV
  Coming soon…
Regression Discontinuity Designs (RDD)
- Sharp RDD
  Coming soon…
- Fuzzy RDD
  Coming soon…
- Spatial RDD
  Coming soon…
- Donut RDD
  Coming soon…
- Half-Donut RDD
  Coming soon…
- Multi-Cutoff RDD
  Coming soon…
- Temporal Discontinuity Designs
  Coming soon…
- Sharp and fuzzy regression kink designs
  Coming soon…
Difference-in-Discontinuities (DiDC) design
Coming soon…
Bunching Approach
Coming soon…
Matching
- Propensity Score Matching (PSM)
  Coming soon…
- Inverse Probability Weighting
  Coming soon…
- Doubly Robust Estimation
  Coming soon…
- Generalized Propensity Score (GPS) Matching
  Coming soon…
- Spatial Matching
  Coming soon…
Machine Learning for Impact Evaluation (Causal Machine Learning)
Coming soon…
Causal Mediation Analysis (Mechanisms)
Coming soon…
Partial Identification and Sensitivity Analysis
Coming soon…
Treatment Evaluation under Interference Effects
Coming soon…

Recommended Causal Inference Books

Causal Inference for The Brave and True by Matheus Facure Alves
Impact Evaluation in Practice - Second Edition by Paul J. Gertler, Sebastian Martinez, Patrick Premand, Laura B. Rawlings & Christel M. J. Vermeersch
Causal Inference: What If by Miguel A. Hern´an & James M. Robins
Causal Inference in Statistics, Social, and Biomedical Sciences by Guido W. Imbens & Donald B. Rubin
Mastering 'Metrics: The Path from Cause to Effect by Joshua D. Angrist, Jörn-Steffen Pischke
Mostly Harmless Econometrics: An Empiricist's Companion by Joshua D. Angrist & Jörn-Steffen Pischke
Introductory Econometrics: A Modern Approach by Jeffrey M. Wooldridge
Handbook on Impact Evaluation: Quantitative Methods and Practices by Shahidur R. Khandker, Gayatri B. Koolwal, & Hussain A. Samad
The Effect by Nick Huntington-Klein
Causal Inference - The Mixtape by Scott Cunningham
Causal Inference for Data Science by Aleix Ruiz de Villa Robert
Causal Inference by Paul R. Rosenbaum
The Book of Why: The New Science of Cause and Effect by Judea Pearl & Dana Mackenzie
Causality: Models, Reasoning and Inference by Judea Pearl
Causal Inference and Discovery in Python by Aleksander Molak
Causal AI by Robert Osazuwa Ness

Recommended General Books

Everydata: The Misinformation Hidden in the Little Data You Consume Every Day by John H. Johnson & Mike Gluck
Thinking, Fast and Slow by Daniel Kahneman
Heuristics and Biases: The Psychology of Intuitive Judgmen by Daniel Kahneman, Thomas Gilovich & Dale Griffin
More general readings coming soon…

Emmanuel Tolani