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SpringerBriefs in Economics

Machine-learning Techniques in Economics

New Tools for Predicting Economic Growth

Authors: Basuchoudhary, Atin, Bang, James T., Sen, Tinni

  • Offers a guide to how machine learning techniques can improve predictive power in answering economic questions 
  • Provides R codes to help guide the researcher in applying machine learning techniques using the R package
  • Uses partial dependence plots to tease out non-linear effects of explanatory variables on the dependent variables
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Buy this book

eBook 44,02 €
price for Spain (gross)
  • ISBN 978-3-319-69014-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 57,19 €
price for Spain (gross)
  • ISBN 978-3-319-69013-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

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. 

Table of contents (6 chapters)

  • Why This Book?

    Basuchoudhary, Atin (et al.)

    Pages 1-6

  • Data, Variables, and Their Sources

    Basuchoudhary, Atin (et al.)

    Pages 7-18

  • Methodology

    Basuchoudhary, Atin (et al.)

    Pages 19-28

  • Predicting a Country’s Growth: A First Look

    Basuchoudhary, Atin (et al.)

    Pages 29-36

  • Predicting Economic Growth: Which Variables Matter

    Basuchoudhary, Atin (et al.)

    Pages 37-56

    Preview Buy Chapter 30,19 €

Buy this book

eBook 44,02 €
price for Spain (gross)
  • ISBN 978-3-319-69014-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 57,19 €
price for Spain (gross)
  • ISBN 978-3-319-69013-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Machine-learning Techniques in Economics
Book Subtitle
New Tools for Predicting Economic Growth
Authors
Series Title
SpringerBriefs in Economics
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
The Author(s)
eBook ISBN
978-3-319-69014-8
DOI
10.1007/978-3-319-69014-8
Softcover ISBN
978-3-319-69013-1
Series ISSN
2191-5504
Edition Number
1
Number of Pages
VI, 94
Number of Illustrations and Tables
1 b/w illustrations, 19 illustrations in colour
Topics