Abstract:

Managing complex systems in which heterogeneous agents act according to non linear behaviors turns into a difficult task. Public policy evaluators are dealing with difficult problems to define efficient public policy management. Until now many methods have been used basing on archaic methodologies or intuitions with no empirical evidences. Simulation seems to be the best option to solve this problem and make efficient decisions in management fields. Due to its flexible and evidence based nature enables a better understanding of the whole system and the effects of their decisions. Moreover, multiple scenes could be simulated while avoiding risky real situations, these characteristics are considered powerful and key functionalities, converting simulation into the best alternative.

The whole simulation process is based on a hybrid framework, two techniques are combined, Agent Based Modelling (ABM), and System Dynamics (SD).This paper will present the context of social simulation, the necessity of evidence based empirical tools for decision making, and a simulation model as an alternative to the evaluation of public policies. The principal objective of the model is policy assessment; two different public policies are analyzed, in order to know which their impact in society is. The methodology followed is: data collection, construction of the model and validation.

In conclusion, it could be stated that necessity of simulation as a tool to evaluate public policies is imminent; an evidence based methodology is needed in order to make decisions which have huge impacts in complex systems as societies are.

Finally, the structure this paper will follow in three steps is: Introduction to social simulation, proposed methodology for the evaluation (theoretical pillars, multi-paradigm framework, and simulation techniques) and construction of the model.

Keywords:

Simulation, Public policies, Management, Evidence-based, Agent Based Modelling, System Dynamics