Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R

This comprehensive and cutting-edge textbook on causal analysis provides a clear and comprehensive introduction to quantitative methods for evaluating causal effects in an increasingly digital and data-driven economy.

With a focus on intuition and motivation, the book covers new trends in machine learning, interaction or interference effects, and recent research designs such as bunching or kink designs.

The author's accessible approach and practical examples using R make this textbook an essential resource for graduate students and researchers in the field.

Don't miss out on this opportunity to gain a competitive edge in your career with this must-have guide to causal analysis!