The second revised and extended edition features two new chapters on some recent development of difference-in-differences. Specifically, chapter 5 introduces advanced difference-in-differences methods when many times are available and treatment can be either time-varying or fixed at a specific time. Chapter 6 introduces the synthetic control method, a treatment effect estimation approach suitable when only one unit is treated. Both chapters present applications using the software Stata.
Giovanni Cerulli is research director at CNR-IRCrES (National Research Council of Italy - Research Institute on Sustainable Economic Growth). He took a degree in Statistics and a PhD in Economic Sciences from Sapienza University of Rome. His research deals with two main subjects: causal inference (including program evaluation), and machine learning. He has developed both theoretical and applied econometric models for program evaluation, including dose-response models, treatment effect estimation with peer effects, and software development for quantitative evaluation purposes. He boasts a consolidated expertise in the evaluation of R&D and innovation policies. Giovanni Cerulli is editor-in-chief of the “International Journal of Computational Economics and Econometrics” (IJCEE), and coordinator of GRAPE (Research Group on the Analysis of Economic Policies). His publications have appeared in prestigious peer-reviewed scientific journals.