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Forecasting from multi-equation econometric micromodels

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Forecasting from multi-equation econometric micromodelsby Jerzy Witold Wisniewski.
作者:	Wisniewski, Jerzy W.
出版者:	Cham :Springer Nature Switzerland :2023.
面頁冊數:	1 online resource (viii, 148 p.) :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Econometrics.
電子資源:	https://doi.org/10.1007/978-3-031-27492-3
ISBN:	9783031274923$q(electronic bk.)

Forecasting from multi-equation econometric micromodels
Wisniewski, Jerzy W.

Forecasting from multi-equation econometric micromodels[electronic resource] /by Jerzy Witold Wisniewski. - Cham :Springer Nature Switzerland :2023. - 1 online resource (viii, 148 p.) :ill. (some col.), digital ;24 cm. - Contributions to economics,2197-7178. - Contributions to economics..

Chapter 1. Single-equation Econometric Model -- Chapter 2. Multi-equation Econometric Models -- Chapter 3. Econometric Forecasts -- Chapter 4. Forecasting From Simple Econometric Micromodels -- Chapter 5. Forecasts From Recursive Econometric Micromodels -- Chapter 6. Forecasting From Econometric Micromodels in the Form of a System of Interdependent Equations.

Forecasting from multi-equation models has very rarely been the focus in econometric literature. In response, this book presents a range of methodologies to approach this complex field and offers readers essential information on forecasting from multi-equation econometric micromodels. In the twentieth century, significant interest in econometric macromodels emerged. These multi-equation models are mostly systems of interdependent equations, most often used to describe the national economies of various countries. The book analyzes econometric forecasting procedures and illustrates them with empirical examples that are based on real economic (mostly business-derived) data. The procedure of forecast building from systems of interdependent equations is presented for two categories of econometric models: models with a feedback effect and models with closed-loop links between interdependent variables. The forecasts obtained via this technique are compared with the results derived from reduced-form equations of the respective econometric model. The author also generalizes the rules of the reduced-recursive (helical, iterative) procedure application, against the backdrop of the proposed method of forecast building from reduced-form equations of systems of interdependent equations. Given its scope, the book will appeal not only to PhD students and researchers, but also undergraduate students and academics in general.

ISBN: 9783031274923$q(electronic bk.)

Standard No.: 10.1007/978-3-031-27492-3doiSubjects--Topical Terms:

182271
Econometrics.

LC Class. No.: HB139

Dewey Class. No.: 330.015195

Forecasting from multi-equation econometric micromodels
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520 $a Forecasting from multi-equation models has very rarely been the focus in econometric literature. In response, this book presents a range of methodologies to approach this complex field and offers readers essential information on forecasting from multi-equation econometric micromodels. In the twentieth century, significant interest in econometric macromodels emerged. These multi-equation models are mostly systems of interdependent equations, most often used to describe the national economies of various countries. The book analyzes econometric forecasting procedures and illustrates them with empirical examples that are based on real economic (mostly business-derived) data. The procedure of forecast building from systems of interdependent equations is presented for two categories of econometric models: models with a feedback effect and models with closed-loop links between interdependent variables. The forecasts obtained via this technique are compared with the results derived from reduced-form equations of the respective econometric model. The author also generalizes the rules of the reduced-recursive (helical, iterative) procedure application, against the backdrop of the proposed method of forecast building from reduced-form equations of systems of interdependent equations. Given its scope, the book will appeal not only to PhD students and researchers, but also undergraduate students and academics in general.
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