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Nonlinear Economic Models

Editor

Listed:
  • John Creedy
  • Vance L. Martin

Abstract

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 macroeconomic labour and finance.

Suggested Citation

  • John Creedy & Vance L. Martin (ed.), 1997. "Nonlinear Economic Models," Books, Edward Elgar Publishing, number 1314.
    • Handle: RePEc:elg:eebook:1314
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    File URL: http://www.e-elgar.com/shop/isbn/9781858986371
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    Citations

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    Cited by:

    1. Koh, Seng Kee & Fong, Wai Mun & Chan, Fabrice, 2007. "A Cardan's discriminant approach to predicting currency crashes," Journal of International Money and Finance, Elsevier, vol. 26(1), pages 131-148, February.
    2. Christian A. Johnson & Rodrigo Vergara, 2005. "The implementation of monetary policy in an emerging economy: the case of Chile," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 20(1), pages 45-62, June.
    3. José Sarabia & Enrique Castillo & Marta Pascual & María Sarabia, 2007. "Bivariate income distributions with lognormal conditionals," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(3), pages 371-383, December.
    4. Chotikapanich, Duangkamon & Griffiths, William E. & Rao, D. S. Prasada, 2007. "Estimating and Combining National Income Distributions Using Limited Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 97-109, January.
    5. Panayiotis Andreou & Chris Charalambous & Spiros Martzoukos, 2006. "Robust Artificial Neural Networks for Pricing of European Options," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 329-351, May.
    6. Fernandes, Marcelo, 2006. "Financial crashes as endogenous jumps: estimation, testing and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 30(1), pages 111-141, January.
    7. Claudia Biancotti & Leandro D'Aurizio & Raffaele Tartaglia-Polcini, 2007. "A neural network architecture for data editing in the Bank of Italy�s business surveys," Temi di discussione (Economic working papers) 612, Bank of Italy, Economic Research and International Relations Area.
    8. Gholamreza Hajargsht & William E. Griffiths & Joseph Brice & D.S. Prasada Rao & Duangkamon Chotikapanich, 2011. "GMM Estimation of Income Distributions from Grouped Data," Department of Economics - Working Papers Series 1129, The University of Melbourne.

    More about this item

    Keywords

    Economics and Finance;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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