Prediction and Causality in Econometrics and Related Topics (Studies in Computational Intelligence, 983)

ISBN 10: 3030770931 / ISBN 13: 9783030770938

Edité par Springer, 2021

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Détails bibliographiques

• Titre: Prediction and Causality in Econometrics and Related Topics (Studies in Computational Intelligence, 983)
• Éditeur: Springer
• Date de parution: 2021
• Langue: anglais
• ISBN à 10 chiffres: 3030770931
• ISBN à 13 chiffres: 9783030770938
• Reliure: Couverture rigide
• État de l'article: New

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Synopsis

This book provides the ultimate goal of economic studies to predict how the economy develops-and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques-including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy.
This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.