Econometrics With Machine Learning

This book helps and promotes the use of machine learning tools and techniques in econometrics and explains how machine learning can enhance and expand the econometrics toolbox in theory and in practice. Throughout the volume, the authors raise and answer six questions: 1) What are the similarities between existing econometric and machine learning techniques? 2) To what extent can machine learning techniques assist econometric investigation? Specifically, how robust or stable is the prediction from machine learning algorithms given the ever-changing nature of human behavior? 3) Can machine learning techniques assist in testing statistical hypotheses and identifying causal relationships in 'big data? 4) How can existing econometric techniques be extended by incorporating machine learning concepts? 5) How can new econometric tools and approaches be elaborated on based on machine learning techniques? 6) Is it possible to develop machine learning techniques furtherand make them even more readily applicable in econometrics?As the data structures in economic and financial data become more complex and models become more sophisticated, the book takes a multidisciplinary approach in developing both disciplines of machine learning and econometrics in conjunction, rather than in isolation.

Econometrics With Machine Learning features in the following genres: Econometrics and economic statistics, Machine learning, Economic theory and philosophy, Macroeconomics

Hardback. £134.99, down from the £149.99 cover price. Not Available.

Econometrics With Machine Learning was written by László Mátyás, Felix Chan and published by Springer an imprint of Springer International Publishing

Econometrics With Machine Learning has 371 pages

Yes it is part of Advanced Studies in Theoretical and Applied Econometrics series

£134.99, reduced from £149.99. Not Available.