Causal Inference in Econometrics

by Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta

Overview

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.

Product Details

ISBN-13:	9783319801087
Publisher:	Springer International Publishing
Publication date:	04/03/2018
Series:	Studies in Computational Intelligence , #622
Edition description:	Softcover reprint of the original 1st ed. 2016
Pages:	638
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Part I Fundamental Theory.- Part II Applications.