Machine-learning Techniques in Economics : New Tools for Predicting Economic Growth

by Atin Basuchoudhary, James T. Bang, Tinni Sen

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.

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Year of publication:	2017
Authors:	Basuchoudhary, Atin ; Bang, James T. ; Sen, Tinni
Publisher:	Cham : Springer
Subject:	Wirtschaftswachstum \| Economic growth \| Prognoseverfahren \| Forecasting model
Description of contents:	Description [swbplus.bsz-bw.de]

Extent:	Online-Ressource (VI, 94 p. 20 illus., 19 illus. in color, online resource)
Series:	SpringerBriefs in Economics SpringerLink / Bücher Springer eBook Collection / Economics and Finance
Type of publication:	Book / Working Paper
Language:	English
ISBN:	978-3-319-69014-8 ; 978-3-319-69013-1
Other identifiers:	10.1007/978-3-319-69014-8 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012398068