Description
Extensive code examples in R, Stata, and Python
Chapters on heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions
An easy-to-read conversational tone
Up-to-date coverage of methods with fast-moving literatures like difference-in-differences
The second edition features a new chapter on partial identification, updated materials, methods, and writing throughout, and additional materials for help navigating the book or in using the book in teaching.






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