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

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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Dibeh, Ghassan (author)
مؤلفون آخرون: Luchinsky, Dmitry G. (author), Luchinskaya, Daria D. (author), Smelyanskiy, Vadim N. (author)
التنسيق: article
منشور في: 2007
الوصول للمادة أونلاين:http://hdl.handle.net/10725/6100
http://dx.doi.org/ 10.1117/12.724764
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
https://www.researchgate.net/profile/Dmitry_Luchinsky/publication/235931090_A_Bayesian_estimation_of_a_stochastic_predator-prey_model_of_economic_fluctuations/links/00463526633bb28b0c000000.pdf
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
الوصف
الملخص: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.