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Partial Identification in Econometrics and Related Topics (Studies in Systems, Decision and Control, 531) - Hardcover
Synopsis
This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will prices change, etc. In general, in science, the usual way to make predictions is:
- to identify a model that best fits the current dynamics, and
- to use this model to predict the future behavior.
In many practical situations―especially in economics―our past experiences are limited. As a result, the authors can only achieve a partial identification. It is therefore important to be able to make predictions based on such partially identified models―which is the main focus of this book. This book emphasizes partial identification techniques, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as game-theoretic approach, interval techniques, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (credit and banking, energy, health, labor, tourism, international trade) to specific issues affecting economy such as ecology, national culture, government regulations, and the existence of shadow economy. This book shows what has been achieved, but even more important are remaining open problems. The authors hope that this book 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. The authors want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments.
The publication of this book―and organization of the conference at which these papers were presented―was supported:
The authors thank the leadership and staff of HUB and VINIF for providing crucial support.
"synopsis" may belong to another edition of this title.
From the Back Cover
This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will prices change, etc. In general, in science, the usual way to make predictions is:
- to identify a model that best fits the current dynamics, and
- to use this model to predict the future behavior.
In many practical situations―especially in economics―our past experiences are limited. As a result, the authors can only achieve a partial identification. It is therefore important to be able to make predictions based on such partially identified models―which is the main focus of this book. This book emphasizes partial identification techniques, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as game-theoretic approach, interval techniques, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (credit and banking, energy, health, labor, tourism, international trade) to specific issues affecting economy such as ecology, national culture, government regulations, and the existence of shadow economy. This book shows what has been achieved, but even more important are remaining open problems. The authors hope that this book 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. The authors want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments.
The publication of this book―and organization of the conference at which these papers were presented―was supported:
- by the Ho Chi Minh University of Banking (HUB), Vietnam, and
- by the Vingroup Innovation Foundation (VINIF).
The authors thank the leadership and staff of HUB and VINIF for providing crucial support.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2024
- ISBN 10 3031591097
- ISBN 13 9783031591099
- BindingHardcover
- LanguageEnglish
- Number of pages746
- EditorNgoc Thach Nguyen, Trung Nguyen Duc, Ha Doan Thanh, Kreinovich Vladik
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Partial Identification in Econometrics and Related Topics (Studies in Systems, Decision and Control, 531)
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Partial Identification in Econometrics and Related Topics
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will pri. Seller Inventory # 1516573289
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Partial Identification in Econometrics and Related Topics (Hardcover)
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Hardcover. Condition: new. Hardcover. This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will prices change, etc. In general, in science, the usual way to make predictions is:to identify a model that best fits the current dynamics, andto use this model to predict the future behavior.In many practical situationsespecially in economicsour past experiences are limited. As a result, the authors can only achieve a partial identification. It is therefore important to be able to make predictions based on such partially identified modelswhich is the main focus of this book. This book emphasizes partial identification techniques, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as game-theoretic approach, interval techniques, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (credit and banking, energy, health, labor, tourism, international trade) to specific issues affecting economy such as ecology, national culture, government regulations, and the existence of shadow economy. This book shows what has been achieved, but even more important are remaining open problems. The authors hope that this book will:inspire practitioners to learn how to apply state-of-the-art techniques, especially techniques of optimal transport statistics, to economic and financial problems, andinspire researchers to further improve the existing techniques and to come up with new techniques for studying economic and financial phenomena. The authors want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments. The publication of this bookand organization of the conference at which these papers were presentedwas supported:by the Ho Chi Minh University of Banking (HUB), Vietnam, and by the Vingroup Innovation Foundation (VINIF). The authors thank the leadership and staff of HUB and VINIF for providing crucial support. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783031591099
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Partial Identification in Econometrics and Related Topics
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will prices change, etc. In general, in science, the usual way to make predictions is: to identify a model that best fits the current dynamics, and to use this model to predict the future behavior. In many practical situations-especially in economics-our past experiences are limited. As a result, the authors can only achieve a partial identification. It is therefore important to be able to make predictions based on such partially identified models-which is the main focus of this book. This book emphasizes partial identification techniques, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as game-theoretic approach, interval techniques, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (credit and banking, energy, health, labor, tourism, international trade) to specific issues affecting economy such as ecology, national culture, government regulations, and the existence of shadow economy. This book shows what has been achieved, but even more important are remaining open problems. The authors hope that this book will: inspire practitioners to learn how to apply state-of-the-art techniques, especially techniques of optimal transport statistics, to economic and financial problems, andinspire researchers to further improve the existing techniques and to come up with new techniques for studying economic and financial phenomena. The authors want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments. The publication of this book-and organization of the conference at which these papers were presented-was supported: by the Ho Chi Minh University of Banking (HUB), Vietnam, and by the Vingroup Innovation Foundation (VINIF). The authors thank the leadership and staff of HUB and VINIF for providing crucial support. 762 pp. Englisch. Seller Inventory # 9783031591099
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Partial Identification in Econometrics and Related Topics
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will prices change, etc. In general, in science, the usual way to make predictions is: to identify a model that best fits the current dynamics, and to use this model to predict the future behavior. In many practical situations-especially in economics-our past experiences are limited. As a result, the authors can only achieve a partial identification. It is therefore important to be able to make predictions based on such partially identified models-which is the main focus of this book. This book emphasizes partial identification techniques, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as game-theoretic approach, interval techniques, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (credit and banking, energy, health, labor, tourism, international trade) to specific issues affecting economy such as ecology, national culture, government regulations, and the existence of shadow economy. This book shows what has been achieved, but even more important are remaining open problems. The authors hope that this book will: inspire practitioners to learn how to apply state-of-the-art techniques, especially techniques of optimal transport statistics, to economic and financial problems, andinspire researchers to further improve the existing techniques and to come up with new techniques for studying economic and financial phenomena. The authors want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments. The publication of this book-and organization of the conference at which these papers were presented-was supported: by the Ho Chi Minh University of Banking (HUB), Vietnam, and by the Vingroup Innovation Foundation (VINIF). The authors thank the leadership and staff of HUB and VINIF for providing crucial support. Seller Inventory # 9783031591099
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Buch. Condition: Neu. Neuware -This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will prices change, etc. In general, in science, the usual way to make predictions is: to identify a model that best fits the current dynamics, andto use this model to predict the future behavior.In many practical situations¿especially in economics¿our past experiences are limited. As a result, the authors can only achieve a partial identification. It is therefore important to be able to make predictions based on such partially identified models¿which is the main focus of this book. This book emphasizes partial identification techniques, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as game-theoretic approach, interval techniques, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (credit and banking, energy, health, labor, tourism, international trade) to specific issues affecting economy such as ecology, national culture, government regulations, and the existence of shadow economy. This book shows what has been achieved, but even more important are remaining open problems. The authors hope that this book will: inspire practitioners to learn how to apply state-of-the-art techniques, especially techniques of optimal transport statistics, to economic and financial problems, andinspire researchers to further improve the existing techniques and to come up with new techniques for studying economic and financial phenomena. The authors want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments.The publication of this book¿and organization of the conference at which these papers were presented¿was supported:by the Ho Chi Minh University of Banking (HUB), Vietnam, andby the Vingroup Innovation Foundation (VINIF).The authors thank the leadership and staff of HUB and VINIF for providing crucial support.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 748 pp. Englisch. Seller Inventory # 9783031591099
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Hardcover. Condition: new. Hardcover. This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will prices change, etc. In general, in science, the usual way to make predictions is:to identify a model that best fits the current dynamics, andto use this model to predict the future behavior.In many practical situationsespecially in economicsour past experiences are limited. As a result, the authors can only achieve a partial identification. It is therefore important to be able to make predictions based on such partially identified modelswhich is the main focus of this book. This book emphasizes partial identification techniques, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as game-theoretic approach, interval techniques, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (credit and banking, energy, health, labor, tourism, international trade) to specific issues affecting economy such as ecology, national culture, government regulations, and the existence of shadow economy. This book shows what has been achieved, but even more important are remaining open problems. The authors hope that this book will:inspire practitioners to learn how to apply state-of-the-art techniques, especially techniques of optimal transport statistics, to economic and financial problems, andinspire researchers to further improve the existing techniques and to come up with new techniques for studying economic and financial phenomena. The authors want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments. The publication of this bookand organization of the conference at which these papers were presentedwas supported:by the Ho Chi Minh University of Banking (HUB), Vietnam, and by the Vingroup Innovation Foundation (VINIF). The authors thank the leadership and staff of HUB and VINIF for providing crucial support. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9783031591099
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Partial Identification in Econometrics and Related Topics (Hardcover)
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ISBN 10: 3031591097
ISBN 13: 9783031591099
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Hardcover. Condition: new. Hardcover. This book covers data processing techniques, with economic and financial application being the unifying theme. To make proper investments in economy, the authors need to have a good understanding of the future trends: how will demand change, how will prices change, etc. In general, in science, the usual way to make predictions is:to identify a model that best fits the current dynamics, andto use this model to predict the future behavior.In many practical situationsespecially in economicsour past experiences are limited. As a result, the authors can only achieve a partial identification. It is therefore important to be able to make predictions based on such partially identified modelswhich is the main focus of this book. This book emphasizes partial identification techniques, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as game-theoretic approach, interval techniques, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (credit and banking, energy, health, labor, tourism, international trade) to specific issues affecting economy such as ecology, national culture, government regulations, and the existence of shadow economy. This book shows what has been achieved, but even more important are remaining open problems. The authors hope that this book will:inspire practitioners to learn how to apply state-of-the-art techniques, especially techniques of optimal transport statistics, to economic and financial problems, andinspire researchers to further improve the existing techniques and to come up with new techniques for studying economic and financial phenomena. The authors want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments. The publication of this bookand organization of the conference at which these papers were presentedwas supported:by the Ho Chi Minh University of Banking (HUB), Vietnam, and by the Vingroup Innovation Foundation (VINIF). The authors thank the leadership and staff of HUB and VINIF for providing crucial support. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9783031591099
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