From Standard Macroeconomics To Non-Linear Macroeconomics
Last period a number of studies try to many demonstrate how the non-linear models can be useful to investigate the behavioural of dynamic economic systems. Using some adequate non-linear models could be a good way to find more refined solutions to actually unsolved problems or ambiguities in economics. Beginning with a short presentation of the simplest non-linear models, then we are demonstrating how the dynamics of complex systems, as the economic system is, could be explained on the base of some more advanced non-linear models and using specific techniques of simulation. We are considering the non-linear models only as an alternative to the stochastic linear models in economics. The conventional explanations of the behaviour of economic system contradict many times the empirical evidence. We are trying to demonstrate that small modifications in the standard linear form of some economic models make more complex and consequently more realistic the behaviour of system simulated on the base of the new non-linear models. Finally, few applications of non-linear models to the study of inflation-unemployment relationship, potentially useful for further empirical studies, are presented.
Volume (Year): 5 (2010)
Issue (Month): 1 (april)
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Daianu, Daniel & Albu, Lucian-Liviu, 1996.
"Strain and the inflation - unemployment relationship: a conceptual and empirical investigation,"
14017, University Library of Munich, Germany.
- Daniel Daianu & Lucian-Liviu Albu, . "Strain and the Inflation - Unemployment Relationship: A Conceptual and Empirical Investigation," Ace Project Memoranda 96/15, Department of Economics, University of Leicester.
- Fischer, Edwin O & Jammernegg, Werner, 1986. "Empirical Investigation of a Catastrophe Theory Extension of the Phillips Curve," The Review of Economics and Statistics, MIT Press, vol. 68(1), pages 9-17, February.
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