Machine Learning for Econometrics - Softcover

Gaillac, Christophe; L'hour, Jrmy

 
9780198918837: Machine Learning for Econometrics
Softcover
ISBN 10: 0198918836 ISBN 13: 9780198918837
Verlag: Oxford University Press, 2025

Inhaltsangabe

Machine Learning for Econometrics is a book for economists seeking to grasp modern machine learning techniques - from their predictive performance to the revolutionary handling of unstructured data - in order to establish causal relationships from data.

The volume covers automatic variable selection in various high-dimensional contexts, estimation of treatment effect heterogeneity, natural language processing (NLP) techniques, as well as synthetic control and macroeconomic forecasting. The foundations of machine learning methods are introduced to provide both a thorough theoretical treatment of how they can be used in econometrics and numerous economic applications, and each chapter contains a series of empirical examples, programs, and exercises to facilitate the reader's adoption and implementation of the techniques.

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Über die Autorin bzw. den Autor

Christophe Gaillac, Associate Professor, University of Geneva,Jérémy L'Hour, Quantitative researcher, Capital Fund Management

Christophe Gaillac is an Associate Professor at the University of Geneva, GSEM. He was a postdoctoral prize research fellow at Oxford University and Nuffield College, and received his PhD in Economics from the Toulouse School of Economics.


Jérémy L'Hour is a quantitative researcher at Capital Fund Management (CFM), a Paris-based systematic hedge fund. He received his PhD in Economics from Université Paris-Saclay.

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Verlag
Oxford University Press
Erscheinungsdatum
2025
Sprache
Englisch
ISBN 10 
0198918836
ISBN 13 
9780198918837
Einband
Taschenbuch
Anzahl der Seiten
352
Kontakt zum Hersteller
ORIGINAL KAISER
https://corp.oup.com/

Via Liguria 4
San Giuliano Milanese
MI
20098
Italien

Weitere beliebte Ausgaben desselben Titels

9780198918820: Machine Learning for Econometrics

Vorgestellte Ausgabe

ISBN 10:  0198918828 ISBN 13:  9780198918820
Verlag: Oxford University Press, 2025
Hardcover