Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R by Huber, Martin
Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R by Huber, Martin

Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R

A comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine learning....
CHF 133.27
CHF 133.27
SKU: 9780262545914
Product Type: Books
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Author: Martin Huber
Format: Paperback
Language: English
Subtotal: CHF 133.27
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Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R by Huber, Martin

Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R

CHF 133.27
Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R by Huber, Martin

Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R

CHF 133.27
Author: Martin Huber
Format: Paperback
Language: English
Description
A comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine learning.

Reasoning 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 designs.

  • Most complete and cutting-edge introduction to causal analysis, including causal machine learning
  • Clean presentation of rigorous material avoids extraneous detail and emphasizes conceptual analogies over statistical notation
  • Supplies a range of applications and practical examples using R


Author: Martin Huber
Publisher: MIT Press
Published: 08/01/2023
Pages: 336
Binding Type: Paperback
Weight: 1.40lbs
ISBN: 9780262545914

About the Author
Martin Huber is Professor of Applied Econometrics at the University of Fribourg, Switzerland, where his research comprises both methodological and applied contributions in the fields of causal analysis and policy evaluation, machine learning, statistics, econometrics, and empirical economics.
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