The purpose of this model is to gain insight into the relationship between poverty and AFDC assistance, to diagnose and explain causes and- on the basis of these findings- to test policy alternatives to alleviate poverty.
Practitioners of system dynamics working in the government sector will often operate in environments filled with administrative complexities and bureaucratic inconsistencies. Some examples of less than ideal conditions encountered in a fairly large policy planning effort are here offered for the student of system dynamics.
The Algarve province in southern Portugal has been undergoing a rapid growth due to a large increase in tourist demand. The mismanagement of the region’s water resources is leading those growth trends to halt. This paper introduces a model developed to provide a needed rational framework for Algarve water resources management, interfacing a system dynamics model with multiobjective programming formulations. The definition of water supply and demand sectors, on a spatially disaggregated basis, is an essential component of the model, with attempts to provide a tool to evaluate the effects of different strategies controlling water supply and demand upon a set of impact variables. To select an optimal strategy one has to solve a multiobjective programming problem, where the components of the objective function are the impact variables referred above. Solution methods include the analytic hierarchy process and the value display approach. The model written in Z-BASIC was run using a simulation period of 10 years.
Case studies of regulatory and social programs suggest that policy systems are dynamic. In the systems described, outcomes depend on how variables interact over time, and feedback among variables--“simultaneous” causation over multiple time periods--is more a rule than an exception. However, the most influential evaluations of public programs are studies using multiple regression. A recognized limitation of multiple regression is its relative insensitivity to multiperiod strategies, feedback among variables, and other dynamics. Accordingly, we maintain, the findings of regression-based and case studies commonly conflict. Simulation modeling can serve as a methodological bridge between case studies and regression-based studies of policy systems, improving theoretical models of the system and providing a way to evaluate the robustness of alternative regression models. The results of some early experiments along these lines are presented.