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.

Nonlinear Econometric Modeling in Time Series
Nonlinear Econometric Modeling in Time Series

Author: William A. Barnett

Publisher: Cambridge University Press

Published: 2000-05-22

Total Pages: 248

ISBN-13: 9780521594240

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This book presents some of the more recent developments in nonlinear time series, including Bayesian analysis and cointegration tests.

Nonlinear Dynamics and Economics
Nonlinear Dynamics and Economics

Author: William A. Barnett

Publisher: Cambridge University Press

Published: 1996-10-28

Total Pages: 426

ISBN-13: 9780521471411

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This 1997 book presents developments in nonlinear economic dynamics along with related research from other fields, including mathematics, statistics, biology, and physics.

Nonlinear Dynamics in Equilibrium Models
Nonlinear Dynamics in Equilibrium Models

Author: John Stachurski

Publisher: Springer Science & Business Media

Published: 2012-01-25

Total Pages: 454

ISBN-13: 3642223974

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Optimal growth theory studies the problem of efficient resource allocation over time, a fundamental concern of economic research. Since the 1970s, the techniques of nonlinear dynamical systems have become a vital tool in optimal growth theory, illuminating dynamics and demonstrating the possibility of endogenous economic fluctuations. Kazuo Nishimura's seminal contributions on business cycles, chaotic equilibria and indeterminacy have been central to this development, transforming our understanding of economic growth, cycles, and the relationship between them. The subjects of Kazuo's analysis remain of fundamental importance to modern economic theory. This book collects his major contributions in a single volume. Kazuo Nishimura has been recognized for his contributions to economic theory on many occasions, being elected fellow of the Econometric Society and serving as an editor of several major journals. Chapter “Introduction” is available open access under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License via link.springer.com.

Weighted Empirical Processes in Dynamic Nonlinear Models
Weighted Empirical Processes in Dynamic Nonlinear Models

Author: Hira L. Koul

Publisher: Springer Science & Business Media

Published: 2002-06-13

Total Pages: 454

ISBN-13: 9780387954769

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This book presents a unified approach for obtaining the limiting distributions of minimum distance. It discusses classes of goodness-of-t tests for fitting an error distribution in some of these models and/or fitting a regression-autoregressive function without assuming the knowledge of the error distribution. The main tool is the asymptotic equi-continuity of certain basic weighted residual empirical processes in the uniform and L2 metrics.

Modern Linear and Nonlinear Econometrics
Modern Linear and Nonlinear Econometrics

Author: Joseph Plasmans

Publisher: Springer

Published: 2011-12-12

Total Pages: 0

ISBN-13: 9781441938312

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The basic characteristic of Modern Linear and Nonlinear Econometrics is that it presents a unified approach of modern linear and nonlinear econometrics in a concise and intuitive way. It covers four major parts of modern econometrics: linear and nonlinear estimation and testing, time series analysis, models with categorical and limited dependent variables, and, finally, a thorough analysis of linear and nonlinear panel data modeling. Distinctive features of this handbook are: -A unified approach of both linear and nonlinear econometrics, with an integration of the theory and the practice in modern econometrics. Emphasis on sound theoretical and empirical relevance and intuition. Focus on econometric and statistical methods for the analysis of linear and nonlinear processes in economics and finance, including computational methods and numerical tools. -Completely worked out empirical illustrations are provided throughout, the macroeconomic and microeconomic (household and firm level) data sets of which are available from the internet; these empirical illustrations are taken from finance (e.g. CAPM and derivatives), international economics (e.g. exchange rates), innovation economics (e.g. patenting), business cycle analysis, monetary economics, housing economics, labor and educational economics (e.g. demand for teachers according to gender) and many others. -Exercises are added to the chapters, with a focus on the interpretation of results; several of these exercises involve the use of actual data that are typical for current empirical work and that are made available on the internet. What is also distinguishable in Modern Linear and Nonlinear Econometrics is that every major topic has a number of examples, exercises or case studies. By this `learning by doing' method the intention is to prepare the reader to be able to design, develop and successfully finish his or her own research and/or solve real world problems.

Nonlinear Models for Economic Decision Processes
Nonlinear Models for Economic Decision Processes

Author: Ionut Purica

Publisher: World Scientific

Published: 2010

Total Pages: 177

ISBN-13: 1848164270

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Using models, developed in one branch of science, to describe similar behaviors encountered in a different one, is the essence of a synergetic approach. A wide range of topics has been developed including Agent-based models, econophysics, socio-economic networks, information, bounded rationality and learning in economics, markets as complex adaptive systems evolutionary economics, multiscale analysis and modeling, nonlinear dynamics and econometrics, physics of risk, statistical and probabilistic methods in economics and finance. Complexity. This publication concentrates on process behavior of economic systems and building models that stem from Haken's, Prigogine's, Taylor's work as well as from nuclear physics models.

Essays in Nonlinear Time Series Econometrics
Essays in Nonlinear Time Series Econometrics

Author: Niels Haldrup

Publisher: OUP Oxford

Published: 2014-06-26

Total Pages: 393

ISBN-13: 0191669547

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This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.

Nonlinear Dynamics in Economics
Nonlinear Dynamics in Economics

Author: Bärbel Finkenstädt

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 167

ISBN-13: 3642468217

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1. 1 Introduction In economics, one often observes time series that exhibit different patterns of qualitative behavior, both regular and irregular, symmetric and asymmetric. There exist two different perspectives to explain this kind of behavior within the framework of a dynamical model. The traditional belief is that the time evolution of the series can be explained by a linear dynamic model that is exogenously disturbed by a stochastic process. In that case, the observed irregular behavior is explained by the influence of external random shocks which do not necessarily have an economic reason. A more recent theory has evolved in economics that attributes the patterns of change in economic time series to an underlying nonlinear structure, which means that fluctua tions can as well be caused endogenously by the influence of market forces, preference relations, or technological progress. One of the main reasons why nonlinear dynamic models are so interesting to economists is that they are able to produce a great variety of possible dynamic outcomes - from regular predictable behavior to the most complex irregular behavior - rich enough to meet the economists' objectives of modeling. The traditional linear models can only capture a limited number of possi ble dynamic phenomena, which are basically convergence to an equilibrium point, steady oscillations, and unbounded divergence. In any case, for a lin ear system one can write down exactly the solutions to a set of differential or difference equations and classify them.

Nonlinear Dynamics, Chaos and Econometrics
Nonlinear Dynamics, Chaos and Econometrics

Author: M. Hashem Pesaran

Publisher: Wiley

Published: 1993-06-01

Total Pages: 256

ISBN-13: 9780471939429

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The empirical modeling of economic time series is dominated by methods that assume linearity of the underlying dynamic economic system. The reason for the adoption of linearity is its analytical and computational simplicity. But dynamic economic systems can be far from linear and the challenge facing applied econometrics in constructing reliable statistical techniques and models for handling dynamic nonlinearities is immense. This book examines and assesses the latest techniques in nonlinear dynamics.