Casual analysis: Impact evaluation and causal machine learning with application in R
- London The MIT Press 2023
- ix, 319 p. Includes bibliographical reference and index
Reasoning about cause and effect—the consequence of doing one thing versus another—is an integral part of our lives as human beings. In an increasingly digital and data-driven economy, the importance of sophisticated causal analysis only deepens. Presenting the most important quantitative methods for evaluating causal effects, this textbook provides graduate students and researchers with a clear and comprehensive introduction to the causal analysis of empirical data.