Machine-learning Techniques in Economics
New Tools for Predicting Economic Growth
Published on 28. December 2017
VI, 94 pages
978-3-319-69014-8 (ISBN)
Description
This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer economic questions. While machine learning itself is not a new idea, advances in computing technology combined with a dawning realization of its applicability to economic questions makes it a new tool for economists.
More details
Series
Edition
1st ed. 2017
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
VI, 94 p. 20 illus., 19 illus. in color.
File size
2,04 MB
ISBN-13
978-3-319-69014-8 (9783319690148)
DOI
10.1007/978-3-319-69014-8
Schweitzer Classification
Other editions
Additional editions
Atin Basuchoudhary | James T. Bang | Tinni Sen
Machine-learning Techniques in Economics
New Tools for Predicting Economic Growth
Book
01/2018
Springer
€69.54
Shipment within 10-15 days
Content
Why this Book?.- Data, Variables, and Their Sources.- Methodology.- Predicting Economic Growth: A First Look.- Predicting Economic Growth: Which Variables Matter?.- Predicting Recessions: What We Learn from Widening the Goalposts.- Epilogue.
