books.md

Causal Inference Books

The following is a list of books in Causal Inference, sorted by publication year.

• Free
• Paid

Note for curators: so far I have included only books whose main focus is causal inference. I might add in the future books that cover causal inference only partially, or books that cover tools required for causal inference (statistics, econometrics, ...).

Free

• Causal Inference for the Brave and True

  • Author: Matheus Facure (Nubank)
  • Year: regularly updated

• Causal Inference: The Mixtape

  • Author: Scott Cunningham (Baylor University)
  • Year: 2021

• The Effect

  • Author: Nick C. Huntington-Klein (Seattle University)
  • Year: 2021
  • Bonus: recordings on Youtube

• Causal Inference: What If

  • Author: Miguel Hernan (Harvard University)
  • Year: 2020

Paid

• Causal Inference in Python

  • Author: Matheus Facure
  • Year: 2023

• Causal Inference and Discovery in Python

  • Author: Aleksander Molak
  • Year: 2023

• Quasi-Experimentation: A Guide to Design and Analysis

  • Author: Charles S. Reichardt
  • Year: 2019

• The Book of Why

  • Author: D. Mackenzie, J. Pearl
  • Year: 2018

• Targeted Learning in Data Science - Causal Inference for Complex Longitudinal Studies

  • Author: Mark J. van der Laan, Sherri Rose
  • Year: 2018

• Elements of Causal Inference: Foundations and Learning Algorithms

  • Author: Jonas Peters, Dominik Janzing, Bernhard Schölkopf
  • Year: 2017

• Statistical Causal Inferences and Their Applications in Public Health Research

  • Author: multiple
  • Year: 2016

• Causal Inference in Statistics: A Primer

  • Author: Judea Pearl, Madelyn Glymour, Nicholas P. Jewell
  • Year: 2016

• Causal Inference for Statistics, Social, and Biomedical Sciences

  • Author: Guido W. Imbens (Stanford University), Donald B. Rubin (Harvard University)
  • Year: 2015

• Counterfactuals and Causal Inference

  • Author: Stephen L. Morgan (Johns Hopkins University), Christopher Winship (Harvard University)
  • Year: 2014

• Handbook of Causal Analysis for Social Research

  • Author: Stephen L. Morgan (Johns Hopkins University)
  • Year: 2013

• Targeted Learning - Causal Inference for Observational and Experimental Data

  • Author: Mark J. van der Laan, Sherri Rose
  • Year: 2011

• Design of Observational Studies

  • Author: Paul R. Rosenbaum
  • Year: 2010

• Mostly Harmless Econometrics: An Empiricist's Companion

  • Author: Joshua D. Angrist, Jörn-Steffen Pischke
  • Year: 2009

• Causality

  • Author: Judea Pearl (University of California, Los Angeles)
  • Year: 2009

• Unified Methods for Censored Longitudinal Data and Causality

  • Authors: Mark J. van der Laan, James M. Robins
  • Year: 2003