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

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. .-- Provided by publisher Front Matter ....Pages i-vi Why This Book? (Atin Basuchoudhary, James T. Bang, Tinni Sen)....Pages 1-6 Data, Variables, and Their Sources (Atin Basuchoudhary, James T. Bang, Tinni Sen)....Pages 7-18 Methodology (Atin Basuchoudhary, James T. Bang, Tinni Sen)....Pages 19-28 Predicting a Country’s Growth: A First Look (Atin Basuchoudhary, James T. Bang, Tinni Sen)....Pages 29-36 Predicting Economic Growth: Which Variables Matter (Atin Basuchoudhary, James T. Bang, Tinni Sen)....Pages 37-56 Predicting Recessions: What We Learn from Widening the Goalposts (Atin Basuchoudhary, James T. Bang, Tinni Sen)....Pages 57-73 Back Matter ....Pages 75-91 Annotation 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