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Econometrics with Machine Learning (Hardcover, 1st ed. 2022) Loot Price: R4,329
Discovery Miles 43 290
Econometrics with Machine Learning (Hardcover, 1st ed. 2022): Felix Chan, Laszlo Matyas

Econometrics with Machine Learning (Hardcover, 1st ed. 2022)

Felix Chan, Laszlo Matyas

Series: Advanced Studies in Theoretical and Applied Econometrics, 53

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Loot Price R4,329 Discovery Miles 43 290 | Repayment Terms: R406 pm x 12*

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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 further and 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. This volume is a must-read for scholars, researchers, students, policy-makers, and practitioners, who are using econometrics in theory or in practice.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Advanced Studies in Theoretical and Applied Econometrics, 53
Release date: September 2022
First published: 2022
Editors: Felix Chan • Laszlo Matyas
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 371
Edition: 1st ed. 2022
ISBN-13: 978-3-03-115148-4
Categories: Books > Business & Economics > Economics > Economic theory & philosophy
Books > Business & Economics > Economics > Macroeconomics > General
Books > Business & Economics > Economics > Econometrics > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 3-03-115148-8
Barcode: 9783031151484

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