Machine-learning techniques in economics : new tools for predicting economic growth

Bibliographic Information

Machine-learning techniques in economics : new tools for predicting economic growth

Atin Basuchoudhary, James T. Bang, Tinni Sen

(Springer briefs in economics)

Springer, c2017

Available at  / 4 libraries

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Note

Includes bibliographical references

Description and Table of Contents

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.

Table of Contents

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.

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Details

  • NCID
    BB25339849
  • ISBN
    • 9783319690131
  • Country Code
    sz
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Cham
  • Pages/Volumes
    vi, 91 p.
  • Size
    24 cm
  • Parent Bibliography ID
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