Basuchoudhary, Atin. Machine-learning Techniques in Economics : New Tools for Predicting Economic Growth / [electronic resource] : / by Atin Basuchoudhary, James T. Bang, Tinni Sen.. — 1st ed. 2017.. — VI, 94 p. 20 illus., 19 illus. in color. : online resource. — (SpringerBriefs in Economics,) 2191-5504. - SpringerBriefs in Economics, .

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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Анотація:
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. .

ISBN: 9783319690148

Standard No.: 10.1007/978-3-319-69014-8 doi

Subjects--Topical Terms:
Economic growth.
Econometrics.
Data mining.
Game theory.
Application software.
Economic Growth.
Econometrics.
Data Mining and Knowledge Discovery.
Game Theory.
Computer Appl. in Social and Behavioral Sciences.

LC Class. No.: HD72-88

Dewey Class. No.: 338.9