Causal Inference in Econometrics

Softcover Nachdruck of the original 1. Auflage 2016
ISBN: 978-3-319-80108-7
Verlag: Springer International Publishing

Buch, Englisch, Band 622, 638 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 972 g

Reihe: Studies in Computational Intelligence

This book is devoted to the analysis of causal inference which  is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume.

To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.

Zielgruppe

Research

Autoren/Hrsg.

Huynh, Van-Nam

Sriboonchitta, Songsak

Kreinovich, Vladik

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Finanz- und Versicherungsmathematik
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik

Inhaltsverzeichnis

Part I Fundamental Theory.- Part II Applications.