Giovanni Cerulli Livres

Advanced micro-econometric techniques are explored in this comprehensive guide aimed at enhancing evidence-based program evaluation in social sciences. The author provides a detailed toolbox for conducting rigorous ex-post evaluations using Stata, covering methods like regression-adjustment, matching, and synthetic control. Each technique is accompanied by a statistical overview and practical examples using real and simulated data, equipping readers with the knowledge to select and apply appropriate methods tailored to specific policy contexts.

The book delves into the essential theoretical concepts of supervised machine learning while showcasing diverse applications through Python, R, and Stata. It strikes a balance between theoretical foundations and practical implementations, enhancing readers' understanding of machine learning techniques across various software platforms.