NONLINEAR OSCILLATIONS IN BUSINESS CYCLE MODEL WITH TIME LAGS

2000 ◽  
Vol 03 (03) ◽  
pp. 603-604 ◽  
Author(s):  
ADAM KRAWIEC ◽  
MAREK SZYDŁOWSKI ◽  
JANUSZ TOBOŁA
Keyword(s):  
Differential Equation ◽  
Business Cycle ◽  
Nonlinear Oscillations ◽  
Equation System ◽  
Hopf Bifurcations ◽  
Time Lags ◽  
Differential Equation System ◽  
Cycle Model ◽  
Business Cycle Model ◽  
Delay Differential

We analyse the Hopf bifurcations in the Kaldor–Kalecki business cycle model represented by a delay differential equation system.

Nonlinear oscillations in business cycle model with time lags☆

2001 ◽  
Vol 12 (3) ◽  
pp. 505-517 ◽  
Author(s):  
Marek Szydłowski ◽  
Adam Krawiec ◽  
Janusz Toboła
Keyword(s):  
Business Cycle ◽  
Nonlinear Oscillations ◽  
Time Lags ◽  
Cycle Model ◽  
Business Cycle Model

scholarly journals Decomposition method for solving a nonlinear business cycle model

2003 ◽  
Vol 45 (2) ◽  
pp. 295-302 ◽  
Author(s):  
Elias Deeba ◽  
Ghassan Dibeh ◽  
Suheil Khuri ◽  
Shishen Xie
Keyword(s):  
Business Cycle ◽  
Decomposition Method ◽  
Type Model ◽  
Cycle Model ◽  
Decomposition Scheme ◽  
Business Cycle Model ◽  
The Business Cycle ◽  
Delay Differential ◽  
Nonlinear Delay Differential Equation ◽  
Nonlinear Delay

AbstractIn this paper we present a Kaleckian-type model of a business cycle based on a nonlinear delay differential equation. A numerical algorithm based on a decomposition scheme is implemented for the approximate solution of the model. The numerical results of the underlying equation show that the business cycle is stable.

BIFURCATIONS IN A STOCHASTIC BUSINESS CYCLE MODEL

2010 ◽  
Vol 20 (12) ◽  
pp. 4111-4118 ◽  
Author(s):  
DONGWEI HUANG ◽  
HONGLI WANG ◽  
YINGFEI YI
Keyword(s):  
Lyapunov Exponent ◽  
Business Cycle ◽  
Hamiltonian Systems ◽  
Largest Lyapunov Exponent ◽  
Hopf Bifurcations ◽  
Cycle Model ◽  
Probability Densities ◽  
Multiplicative Ergodic Theorem ◽  
Business Cycle Model ◽  
Parameter Values

We introduce a stochastic business cycle model and study the underlying stochastic Hopf bifurcations with respect to probability densities at different parameter values. Our analysis is based on the calculation of the largest Lyapunov exponent via multiplicative ergodic theorem and the theory of boundary analysis for quasi-nonintegrable Hamiltonian systems. Some numerical simulations of the model are performed.

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