Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications

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Causal Analysis by Martin Huber

"A graduate-level textbook for causal inference/causal analysis in economics/econometrics courses"--

FORMAT
Paperback LANGUAGE
English CONDITION
Brand New Publisher Description

A comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine learning.A comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine about cause and effect-the consequence of doing one thing versus another-is an integral part of our lives as human beings. In an increasingly digital and data-driven economy, the importance of sophisticated causal analysis only deepens. Presenting the most important quantitative methods for evaluating causal effects, this textbook provides graduate students and researchers with a clear and comprehensive introduction to the causal analysis of empirical data. Martin Huber's accessible approach highlights the intuition and motivation behind various methods while also providing formal discussions of key concepts using statistical notation. Causal Analysis covers several methodological developments not covered in other texts, including new trends in machine learning, the evaluation of interaction or interference effects, and recent research designs such as bunching or kink complete and cutting-edge introduction to causal analysis, including causal machine learningClean presentation of rigorous material avoids extraneous detail and emphasizes conceptual analogies over statistical notationSupplies a range of applications and practical examples using R

Table of Contents

1 Introduction 1
2 Causality and No Causality 11
3 Social Experiments and Linear Regression 19
4 Selection on Observables 65
5 Casual Machine Learning 137
6 Instrumental Variables 169
7 Difference-in-Differences 195
8 Synthetic Controls 219
9 Regression Discontinuity, Kink, and Bunching Designs 231
10 Partial Identification and Sensitivity Analysis 255
11 Treatment Evaluation under Interference Effects 271
12 Conclusion 285
References 287
Index 311

Prizes

2024 PROSE Award Finalist: Computing and Information Sciences

Details ISBN0262545918 Author Martin Huber Short Title Causal Analysis Language English Year 2023 ISBN-10 0262545918 ISBN-13 9780262545914 Format Paperback Publication Date 2023-08-01 Subtitle Impact Evaluation and Causal Machine Learning with Applications in R Pages 336 Publisher MIT Press Ltd Imprint MIT Press Country of Publication United States US Release Date 2023-08-01 UK Release Date 2023-08-01 Illustrations 40 BLACK AND WHITE ILLUS. Audience General DEWEY 300.72 Country of Origin US Product Class Description Economics: Professional & General AU Release Date 2023-09-05 NZ Release Date 2023-09-05
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