Advances in Non-linear Economic Modeling

Advances in Non-linear Economic Modeling

Author: Frauke Schleer-van Gellecom

Publisher: Springer Science & Business Media

Published: 2013-12-11

Total Pages: 268

ISBN-13: 3642420397

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In recent years nonlinearities have gained increasing importance in economic and econometric research, particularly after the financial crisis and the economic downturn after 2007. This book contains theoretical, computational and empirical papers that incorporate nonlinearities in econometric models and apply them to real economic problems. It intends to serve as an inspiration for researchers to take potential nonlinearities in account. Researchers should be aware of applying linear model-types spuriously to problems which include non-linear features. It is indispensable to use the correct model type in order to avoid biased recommendations for economic policy.


Book Synopsis Advances in Non-linear Economic Modeling by : Frauke Schleer-van Gellecom

Download or read book Advances in Non-linear Economic Modeling written by Frauke Schleer-van Gellecom and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years nonlinearities have gained increasing importance in economic and econometric research, particularly after the financial crisis and the economic downturn after 2007. This book contains theoretical, computational and empirical papers that incorporate nonlinearities in econometric models and apply them to real economic problems. It intends to serve as an inspiration for researchers to take potential nonlinearities in account. Researchers should be aware of applying linear model-types spuriously to problems which include non-linear features. It is indispensable to use the correct model type in order to avoid biased recommendations for economic policy.


Recent Advances in Estimating Nonlinear Models

Recent Advances in Estimating Nonlinear Models

Author: Jun Ma

Publisher: Springer Science & Business Media

Published: 2013-09-24

Total Pages: 308

ISBN-13: 1461480604

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Nonlinear models have been used extensively in the areas of economics and finance. Recent literature on the topic has shown that a large number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and estimating nonlinear time series models, and these have typically taken the form of Threshold Autoregression (TAR) models, Exponential Smooth Transition (ESTAR) models, and Markov Switching (MS) models, among several others. This edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. It features cutting-edge research from leading academics in economics, finance, and business management, and will focus on such topics as Zero-Information-Limit-Conditions, using Markov Switching Models to analyze economics series, and how best to distinguish between competing nonlinear models. Principles and techniques in this book will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.


Book Synopsis Recent Advances in Estimating Nonlinear Models by : Jun Ma

Download or read book Recent Advances in Estimating Nonlinear Models written by Jun Ma and published by Springer Science & Business Media. This book was released on 2013-09-24 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear models have been used extensively in the areas of economics and finance. Recent literature on the topic has shown that a large number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and estimating nonlinear time series models, and these have typically taken the form of Threshold Autoregression (TAR) models, Exponential Smooth Transition (ESTAR) models, and Markov Switching (MS) models, among several others. This edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. It features cutting-edge research from leading academics in economics, finance, and business management, and will focus on such topics as Zero-Information-Limit-Conditions, using Markov Switching Models to analyze economics series, and how best to distinguish between competing nonlinear models. Principles and techniques in this book will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.


Optimization in Economics and Finance

Optimization in Economics and Finance

Author: Bruce D. Craven

Publisher: Springer Science & Business Media

Published: 2005-10-24

Total Pages: 174

ISBN-13: 0387242805

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Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.


Book Synopsis Optimization in Economics and Finance by : Bruce D. Craven

Download or read book Optimization in Economics and Finance written by Bruce D. Craven and published by Springer Science & Business Media. This book was released on 2005-10-24 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.


Nonlinearities in Economics

Nonlinearities in Economics

Author: Giuseppe Orlando

Publisher: Springer Nature

Published: 2021-08-31

Total Pages: 361

ISBN-13: 3030709825

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This interdisciplinary book argues that the economy has an underlying non-linear structure and that business cycles are endogenous, which allows a greater explanatory power with respect to the traditional assumption that dynamics are stochastic and shocks are exogenous. The first part of this work is formal-methodological and provides the mathematical background needed for the remainder, while the second part presents the view that signal processing involves construction and deconstruction of information and that the efficacy of this process can be measured. The third part focuses on economics and provides the related background and literature on economic dynamics and the fourth part is devoted to new perspectives in understanding nonlinearities in economic dynamics: growth and cycles. By pursuing this approach, the book seeks to (1) determine whether, and if so where, common features exist, (2) discover some hidden features of economic dynamics, and (3) highlight specific indicators of structural changes in time series. Accordingly, it is a must read for everyone interested in a better understanding of economic dynamics, business cycles, econometrics and complex systems, as well as non-linear dynamics and chaos theory.


Book Synopsis Nonlinearities in Economics by : Giuseppe Orlando

Download or read book Nonlinearities in Economics written by Giuseppe Orlando and published by Springer Nature. This book was released on 2021-08-31 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This interdisciplinary book argues that the economy has an underlying non-linear structure and that business cycles are endogenous, which allows a greater explanatory power with respect to the traditional assumption that dynamics are stochastic and shocks are exogenous. The first part of this work is formal-methodological and provides the mathematical background needed for the remainder, while the second part presents the view that signal processing involves construction and deconstruction of information and that the efficacy of this process can be measured. The third part focuses on economics and provides the related background and literature on economic dynamics and the fourth part is devoted to new perspectives in understanding nonlinearities in economic dynamics: growth and cycles. By pursuing this approach, the book seeks to (1) determine whether, and if so where, common features exist, (2) discover some hidden features of economic dynamics, and (3) highlight specific indicators of structural changes in time series. Accordingly, it is a must read for everyone interested in a better understanding of economic dynamics, business cycles, econometrics and complex systems, as well as non-linear dynamics and chaos theory.


Optimization in Economics and Finance

Optimization in Economics and Finance

Author: Bruce Desmond Craven

Publisher:

Published: 2007

Total Pages:

ISBN-13:

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Many optimization questions arise in economics and finance; an important example of this is the society's choice of the optimum state of the economy (the social choice problem). This book the usual optimization techniques, in a form that may be adopted for modeling social choice problems. Problems discussed include: when is an optimum reached; when is it unique; relaxation of the conventional convex (or concave) assumptions on an economic model; associated mathematical concepts such as invex and quasimax; multiobjective optimal control models; and related computational methods and programs. These techniques are applied to economic growth models (including small stochastic perturbations), finance and financial investment models (and the interaction between financial and production variables), modeling sustainability over long time horizons, boundary (transversality) conditions, and models with several conflicting objectives. Although the applications are general and illustrative, the models in this book provide examples of possible models for a society's social choice for an allocation that maximizes welfare and utilization of resources. As well as using existing computer programs for optimization of models, a new computer program, named SCOM, is presented in this book for computing social choice models by optimal control.


Book Synopsis Optimization in Economics and Finance by : Bruce Desmond Craven

Download or read book Optimization in Economics and Finance written by Bruce Desmond Craven and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Many optimization questions arise in economics and finance; an important example of this is the society's choice of the optimum state of the economy (the social choice problem). This book the usual optimization techniques, in a form that may be adopted for modeling social choice problems. Problems discussed include: when is an optimum reached; when is it unique; relaxation of the conventional convex (or concave) assumptions on an economic model; associated mathematical concepts such as invex and quasimax; multiobjective optimal control models; and related computational methods and programs. These techniques are applied to economic growth models (including small stochastic perturbations), finance and financial investment models (and the interaction between financial and production variables), modeling sustainability over long time horizons, boundary (transversality) conditions, and models with several conflicting objectives. Although the applications are general and illustrative, the models in this book provide examples of possible models for a society's social choice for an allocation that maximizes welfare and utilization of resources. As well as using existing computer programs for optimization of models, a new computer program, named SCOM, is presented in this book for computing social choice models by optimal control.


Dynamic Nonlinear Econometric Models

Dynamic Nonlinear Econometric Models

Author: Benedikt M. Pötscher

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 307

ISBN-13: 3662034867

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Many relationships in economics, and also in other fields, are both dynamic and nonlinear. A major advance in econometrics over the last fifteen years has been the development of a theory of estimation and inference for dy namic nonlinear models. This advance was accompanied by improvements in computer technology that facilitate the practical implementation of such estimation methods. In two articles in Econometric Reviews, i.e., Pötscher and Prucha {1991a,b), we provided -an expository discussion of the basic structure of the asymptotic theory of M-estimators in dynamic nonlinear models and a review of the literature up to the beginning of this decade. Among others, the class of M-estimators contains least mean distance estimators (includ ing maximum likelihood estimators) and generalized method of moment estimators. The present book expands and revises the discussion in those articles. It is geared towards the professional econometrician or statistician. Besides reviewing the literature we also presented in the above men tioned articles a number of then new results. One example is a consis tency result for the case where the identifiable uniqueness condition fails.


Book Synopsis Dynamic Nonlinear Econometric Models by : Benedikt M. Pötscher

Download or read book Dynamic Nonlinear Econometric Models written by Benedikt M. Pötscher and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many relationships in economics, and also in other fields, are both dynamic and nonlinear. A major advance in econometrics over the last fifteen years has been the development of a theory of estimation and inference for dy namic nonlinear models. This advance was accompanied by improvements in computer technology that facilitate the practical implementation of such estimation methods. In two articles in Econometric Reviews, i.e., Pötscher and Prucha {1991a,b), we provided -an expository discussion of the basic structure of the asymptotic theory of M-estimators in dynamic nonlinear models and a review of the literature up to the beginning of this decade. Among others, the class of M-estimators contains least mean distance estimators (includ ing maximum likelihood estimators) and generalized method of moment estimators. The present book expands and revises the discussion in those articles. It is geared towards the professional econometrician or statistician. Besides reviewing the literature we also presented in the above men tioned articles a number of then new results. One example is a consis tency result for the case where the identifiable uniqueness condition fails.


Non-Linear Time Series Models in Empirical Finance

Non-Linear Time Series Models in Empirical Finance

Author: Philip Hans Franses

Publisher: Cambridge University Press

Published: 2000-07-27

Total Pages: 299

ISBN-13: 0521770416

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This 2000 volume reviews non-linear time series models, and their applications to financial markets.


Book Synopsis Non-Linear Time Series Models in Empirical Finance by : Philip Hans Franses

Download or read book Non-Linear Time Series Models in Empirical Finance written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2000-07-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2000 volume reviews non-linear time series models, and their applications to financial markets.


Nonlinear Dynamical Systems in Economics

Nonlinear Dynamical Systems in Economics

Author: Marji Lines

Publisher: Springer Science & Business Media

Published: 2007-03-23

Total Pages: 238

ISBN-13: 3211380434

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Many problems in theoretical economics are mathematically formalized as dynam ical systems of difference and differential equations. In recent years a truly open approach to studying the dynamical behavior of these models has begun to make its way into the mainstream. That is, economists formulate their hypotheses and study the dynamics of the resulting models rather than formulating the dynamics and studying hypotheses that could lead to models with such dynamics. This is a great progress over using linear models, or using nonlinear models with a linear approach, or even squeezing economic models into well-studied nonlinear systems from other fields. There are today a number of economic journals open to publishing this type of work and some of these have become important. There are several societies which have annual meetings on the subject and participation at these has been growing at a good rate. And of course there are methods and techniques avail able to a more general audience, as well as a greater availability of software for numerical and graphical analysis that makes this type of research even more excit ing. The lecturers for the Advanced School on Nonlinear Dynamical Systems in Economics, who represent a wide selection of the research areas to which the the ory has been applied, agree on the importance of simulations and computer-based analysis. The School emphasized computer applications of models and methods, and all contributors ran computer lab sessions.


Book Synopsis Nonlinear Dynamical Systems in Economics by : Marji Lines

Download or read book Nonlinear Dynamical Systems in Economics written by Marji Lines and published by Springer Science & Business Media. This book was released on 2007-03-23 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many problems in theoretical economics are mathematically formalized as dynam ical systems of difference and differential equations. In recent years a truly open approach to studying the dynamical behavior of these models has begun to make its way into the mainstream. That is, economists formulate their hypotheses and study the dynamics of the resulting models rather than formulating the dynamics and studying hypotheses that could lead to models with such dynamics. This is a great progress over using linear models, or using nonlinear models with a linear approach, or even squeezing economic models into well-studied nonlinear systems from other fields. There are today a number of economic journals open to publishing this type of work and some of these have become important. There are several societies which have annual meetings on the subject and participation at these has been growing at a good rate. And of course there are methods and techniques avail able to a more general audience, as well as a greater availability of software for numerical and graphical analysis that makes this type of research even more excit ing. The lecturers for the Advanced School on Nonlinear Dynamical Systems in Economics, who represent a wide selection of the research areas to which the the ory has been applied, agree on the importance of simulations and computer-based analysis. The School emphasized computer applications of models and methods, and all contributors ran computer lab sessions.


Nonlinear Econometric Modeling in Time Series

Nonlinear Econometric Modeling in Time Series

Author: William A. Barnett

Publisher: Cambridge University Press

Published: 2006-11-02

Total Pages: 0

ISBN-13: 9780521028684

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Nonlinear Econometric Modeling in Time Series Analysis presents recent developments in this important area of research. This is the first volume to focus on the more recent literature on nonlinear time series. Specific topics covered with respect to nonlinearity include cointegration tests, risk-related asymmetries, structural breaks and outliers, Bayesian analysis with a threshold, consistency and asymptotic normality, asymptotic inference, and error-correction models.


Book Synopsis Nonlinear Econometric Modeling in Time Series by : William A. Barnett

Download or read book Nonlinear Econometric Modeling in Time Series written by William A. Barnett and published by Cambridge University Press. This book was released on 2006-11-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Econometric Modeling in Time Series Analysis presents recent developments in this important area of research. This is the first volume to focus on the more recent literature on nonlinear time series. Specific topics covered with respect to nonlinearity include cointegration tests, risk-related asymmetries, structural breaks and outliers, Bayesian analysis with a threshold, consistency and asymptotic normality, asymptotic inference, and error-correction models.


Nonlinear Economic Models

Nonlinear Economic Models

Author: John Creedy

Publisher: Edward Elgar Publishing

Published: 1997

Total Pages: 312

ISBN-13:

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A sequel to Creedy and Martin's (eds.) Chaos and Nonlinear Models (1994). Compiles recent developments in such techniques as cross- sectional studies of income distribution and discrete choice models, time series models of exchange rate dynamics and jump processes, and artificial neural networks and genetic algorithms of financial markets. Also considers the development of theoretical models and estimating and testing methods, with a wide range of applications in microeconomics, macroeconomics, labor, and finance. Annotation copyrighted by Book News, Inc., Portland, OR


Book Synopsis Nonlinear Economic Models by : John Creedy

Download or read book Nonlinear Economic Models written by John Creedy and published by Edward Elgar Publishing. This book was released on 1997 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: A sequel to Creedy and Martin's (eds.) Chaos and Nonlinear Models (1994). Compiles recent developments in such techniques as cross- sectional studies of income distribution and discrete choice models, time series models of exchange rate dynamics and jump processes, and artificial neural networks and genetic algorithms of financial markets. Also considers the development of theoretical models and estimating and testing methods, with a wide range of applications in microeconomics, macroeconomics, labor, and finance. Annotation copyrighted by Book News, Inc., Portland, OR