Abstract:
Repetitive Stochastic Guesstimation (RSG) is a probabilistic algorithm introduced in Charemza (1996) which mimics the usual guessing of the parameters involved in a complex large macroeconomic model. The paper analyzes the objective function employed by RSG and it establishes sufficient conditions on the RSG components in order to achieve global convergence for a specific task, namely the linear regression problem.