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
- Writing Science
- Practical Tips for Writing and Publishing Applied Economics Papers
- The Introduction Formula in Economics
- The Middle Bits Formula
- The Conclusion Formula
- How to Write Applied Papers in Economics
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…
- Classical DiD (Canonical 2x2 DiD)
- 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…
- Canonical Synthetic Control Method (SCM)
- 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…
- Standard (two-stage Least squares) IV
- 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…
- Sharp RDD
- 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…
- Propensity Score Matching (PSM)
- 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…
