Nonlinear Economic Models

Cross-sectional, Time Series and Neural Network Applications

Inbunden, Engelska, 1997

1 978 kr

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Beskrivning

Nonlinear modelling has become increasingly important and widely used in economics. This valuable book brings together recent advances in the area including contributions covering cross-sectional studies of income distribution and discrete choice models, time series models of exchange rate dynamics and jump processes, and artificial neural network and genetic algorithm models of financial markets. Attention is given to the development of theoretical models as well as estimation and testing methods with a wide range of applications in micro and macroeconomics, labour and finance.The book provides valuable introductory material that is accessible to students and scholars interested in this exciting research area, as well as presenting the results of new and original research. Nonlinear Economic Models provides a sequel to Chaos and Nonlinear Models in Economics by the same editors.

Produktinformation

Utgivningsdatum:1997-10-09
Mått:156 x 234 x undefined mm
Format:Inbunden
Språk:Engelska
Förlag:Edward Elgar Publishing Ltd
ISBN:9781858986371

Utforska kategorier

Mikroekonomi inom Ekonomi och Ledarskap
Systemvetenskap och AI inom Data och IT
Tillämpad matematik inom Naturvetenskap och teknik

Mer om författaren

Edited by John Creedy, Wellington School of Business and Government, Victoria University of Wellington, New Zealand and Vance L. Martin, former Associate Professor in Economics, University of Melbourne, Australia

Recensioner i media

'This collection provides valuable introductory material that is accessible to students and scholars interested in this research area.'

Innehållsförteckning

Contents: Part I: Introduction 1. Nonlinear Modelling: An Introduction Part II: Cross-sectional Applications 2. A Model of Income Distribution 3. Truncated Distribution Families 4. Betit: A Flexible Binary Choice Model 5. Estimation of Generalised Distributions 6. Age and the Distribution of Earnings 7. Count Data and Discrete Distributions Part III: Time Series Applications 8. A Model of the Real Exchange Rate 9. Jump Models and Higher Moments 10. A Topological Test of Chaos 11. Genetic Algorithms and Trading Rules Part IV: Neural Network Applications 12. Artificial Neural Networks 13. An ANN Model of the Stock Market 14. Exchange Rate Forecasting Models Index