Chapter 1 — Felix Chan, Laszlo Matyas, and TBA: Linear Econometric Models with Machine Learning [Comprehensive Survey of Model Selection in Linear Models]
Chapter 2 — Ben Weiern Yeo, Mark Harris, Ranjodh Singh and Felix Chan : Non-linear Econometric Models with Machine Learning [Comprehensive Survey of Model Selection in Non-linear Models]
Chapter 3 5 — William Crown: Causal Inference with Non-Randomized Health Care Data Using Machine Learning [Machine Learning and Causality]
Chapter 4 — Marcelo Cunha Medeiros, TBA: Forecasting with Machine Learning Methods [Comprehensive survey of Econometric Forecasting and Prediction]
Chapter 5 3 — Yu-Chin Hsu, Robert Lieli and Agoston Reguly: Machine Learning in Treatment Effect Estimation [Survey of Policy Evaluation]
Chapter 6 — Oliver Kiss and Gyorgy Ruzicska: Econometrics with Machine Learning Using Network Data
Chapter 7 — Samuele Centorrino, Jean-Pierre Florens and Jean-Michel Loubes: Fairness in Machine Learning and in Econometrics
Chapter 8 — Ekaterina Seregina: Graphical Models and their Interactions with Machine Learning in the Context of Eonomics and Finance
Chapter 9 — Walter Sosa Escudero: Poverty, Inequality and Development Studies with Machine Learning
Chapter 10 — Jantje Sönksen: Machine Learning for Asset Pricing