Dr. Ghassan Dibeh Profile

Dr. Ghassan Dibeh

at Lebanese American Univ

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Proceedings Article | 15 June 2007 Paper

A Bayesian estimation of a stochastic predator-prey model of economic fluctuations

Ghassan Dibeh, Dmitry Luchinsky, Daria Luchinskaya, Vadim Smelyanskiy

Proceedings Volume 6601, 660115 (2007) https://doi.org/10.1117/12.724764

KEYWORDS: Data modeling, Stochastic processes, Motion models, Diffusion, Data analysis, Systems modeling, Differential equations, Databases, Electroluminescence, Roads

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In this paper, we develop a Bayesian framework for the empirical estimation of the parameters of one of the best known nonlinear models of the business cycle: The Marx-inspired model of a growth cycle introduced by R. M. Goodwin. The model predicts a series of closed cycles representing the dynamics of labor's share and the employment rate in the capitalist economy. The Bayesian framework is used to empirically estimate a modified Goodwin model. The original model is extended in two ways. First, we allow for exogenous periodic variations of the otherwise steady growth rates of the labor force and productivity per worker. Second, we allow for stochastic variations of those parameters. The resultant modified Goodwin model is a stochastic predator-prey model with periodic forcing. The model is then estimated using a newly developed Bayesian estimation method on data sets representing growth cycles in France and Italy during the years 1960-2005. Results show that inference of the parameters of the stochastic Goodwin model can be achieved. The comparison of the dynamics of the Goodwin model with the inferred values of parameters demonstrates quantitative agreement with the growth cycle empirical data.

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