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

ISBN 10: 3030770931 / ISBN 13: 9783030770938

Editore: Springer, 2021

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1st ed. 2022 edition NO-PA16APR2015-KAP.

Codice articolo 26387427529

Dati bibliografici

• Titolo: Prediction and Causality in Econometrics and Related Topics (Studies in Computational Intelligence, 983)
• Editore: Springer
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 3030770931
• ISBN 13: 9783030770938
• Rilegatura: Rilegato
• Condizione: New

Descrizione articolo

Riassunto

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.