Econometrics with Machine Learning


The Book's Motivation

Abstracts (preliminary, some modifications may be done to avoid overlaps, etc.):
Chapter 1, July 27 version: PDF
Chapter 2, July 29 version: PDF
Chapter 3,
Chapter 4, July 27 version: PDF
Chapter 5,
Chapter 6, June 30 version: PDF
Chapter 7, July 28 version: PDF
Chapter 8,
Chapter 9,
Chapter 10, July 24 version: PDF
Chapter 11, July 22 version: DOC
Chapter 12,
Chapter 13,

Timeline:
1. An indicative and informative title for the contributions, as soon as on board in order to avoid unnecessary overlaps between the chapters. DONE
2. Finalise the list of chapters and contributors: April 2021. DONE
3. Get a (2-3 pages) outline for each chapter: July (end of) 2021 (will then contact and deal with the publisher). UNDER WAY
4. First full draft for all chapters: January (end of) 2022.
5. Final version for all chapters: May 2022.
6. Expected publication: Fall 2022.

Chapters:
Chapter 1 — Felix Chan, Laszlo Matyas, and TBA: (Comprehensive Survey of) Model Selection in Linear Models
Chapter 2 — Ben Weiern Yeo, Mark Harris, Ranjodh Singh and Felix Chan : (Comprehensive Survey of) Model Selection in Non-linear Models
Chapter 3 — Esfandiar Maasoumi and Ali Habibnia: Big Data: Econometric Modelling and Machine Learning
Chapter 4 — William Crown: Machine Learning and Causality
Chapter 5 — Marcelo Cunha Medeiros, TBA: (Comprehensive survey of) Econometric Forecasting and Prediction
Chapter 6 — Qingliang Fan, Yu-Chin Hsu and Robert Lieli: (Comprehensive survey of) Policy Evaluation
Chapter 7 — Oliver Kiss and Gyorgy Ruzicska: Econometrics with Machine Learning Using Network Data
Chapter 8 — Samuele Centorrino, Jean-Pierre Florens and Jean-Michel Loubes: Fairness in Machine Learning and in Econometrics
Chapter 9 — Amit K Gandhi: Machine Learning for Instrumental Variable and Structural Estimation Problems
Chapter 10 — Ekaterina Seregina: Graphical Models and their Interactions with Machine Learning in the Context of Eonomics and Finance
Chapter 11 — Walter Sosa Escudero: Poverty, Inequality and Development Studies with Machine Learning
Chapter 12 — Jantje Sönksen: Machine Learning for Asset Pricing
Chapter 13 — Daniel Marable, TBA: Practical Issues on Machine Learning Algorithms from a Computational Perspective