Machine learning for econometrics
Gaillac, Christophe
Machine learning for econometrics - New York Oxford University Press 2025 - xiv, 338 p. Includes bibliographical reference and index
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.
9780198918837
Textual
Machine learning for econometrics - New York Oxford University Press 2025 - xiv, 338 p. Includes bibliographical reference and index
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.
9780198918837
Textual