Nonlinear Economic Models
Cross-sectional, Time Series and Neural Network Applications
Edward Elgar Publishing
Published on 9. October 1997
Book
Hardback
304 pages
978-1-85898-637-1 (ISBN)
Description
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.
Reviews / Votes
'This collection provides valuable introductory material that is accessible to students and scholars interested in this research area.' -- Business HorizonsMore details
Language
English
Place of publication
Cheltenham
United Kingdom
Target group
College/higher education
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-85898-637-1 (9781858986371)
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Schweitzer Classification
Persons
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
Content
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