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|a Basuchoudhary, Atin.
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|a Machine-learning Techniques in Economics
|h [electronic resource] :
|b New Tools for Predicting Economic Growth /
|c by Atin Basuchoudhary, James T. Bang, Tinni Sen.
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| 250 |
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|a 1st ed. 2017.
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| 264 |
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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| 300 |
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|a VI, 94 p. 20 illus., 19 illus. in color.
|b online resource.
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|a 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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| 520 |
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|a 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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|a Data mining.
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|a Game theory.
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