Overview
- Covers data processing techniques, with economic and financial application being the unifying theme
- Describes econometric techniques, ranging from traditional statistical techniques to more innovative ones
- Emphasizes techniques of optimal transport statistics
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 483)
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About this book
This volume emphasizes techniques of optimal transport statistics, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as quantiles (in particular, multidimensional quantiles), maximum entropy approach, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (construction, credit and banking, energy, health, labor, textile, tourism, international trade) to specific issues affecting economy such as bankruptcy, effect of Covid-19 pandemic, effect of pollution, effect of gender, cryptocurrencies, and the existence of shadow economy. Papers presented in this volume also cover data processing techniques, with economic and financial application being the unifying theme. This volume shows what has been achieved, but even more important are remaining open problems. We hope that this volume will: inspire practitioners to learn how to apply state-of-the-art techniques, especially techniques of optimal transport statistics, to economic and financial problems, and inspire researchers to further improve the existing techniques and to come up with new techniques for studying economic and financial phenomena.
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Table of contents (49 chapters)
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Back Matter
Editors and Affiliations
Bibliographic Information
Book Title: Optimal Transport Statistics for Economics and Related Topics
Editors: Nguyen Ngoc Thach, Vladik Kreinovich, Doan Thanh Ha, Nguyen Duc Trung
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-031-35763-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Hardcover ISBN: 978-3-031-35762-6Published: 31 October 2023
Softcover ISBN: 978-3-031-35765-7Due: 13 November 2024
eBook ISBN: 978-3-031-35763-3Published: 31 October 2023
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: XI, 700
Number of Illustrations: 16 b/w illustrations, 101 illustrations in colour
Topics: Mathematical and Computational Engineering, Industrial Chemistry/Chemical Engineering, Energy Systems