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Simulating Policy Change through Discrete Events


Policy process research is about studying the ongoing sequences of change.  Change can be thought of in many ways.  One way is to think of change as about effects (the size of the change).  Another way is to think of change as about the mechanisms (how change occurs). 

Recently, scholars working within the Advocacy Coalition Framework (ACF) have devoted their attention to the mechanisms underlying the theoretical logic supported by the framework, including coalition formation, learning, and policy change (e.g., Nohrstedt, 2011).  Such effort might include the study of the flow of new information and its effects on coalition behavior as well as on how shifting resources affect the likelihood of policy change.  However, the intervening links connecting any change observation are still largely unknown and need to be clearly articulated theoretically and tested empirically.

copy_of_Sabatier_1988[1] (2).png

Figure 1: Re-creation of Sabatier model (1988)

Adapted_Sabatier_1988[1] (2).png

Figure 2: Modified version of Sabatier (1988) model for simulation

This project on Simulating Policy Change seeks to develop into a formal model Paul Sabatier’s informal model (1988, pg X) of how two coalitions react to new information, engage in analytical debates, and, possibly, adopt new policies.  A current approach utilizes discrete event simulation to assess how two coalitions react to new information leading to policy change within the ACF. Discrete event simulation creates randomly generated information and uses a detailed flow diagram and research based decision logic to illustrate how coalitions react to new information under varying conditions of dominance over one another and states of collaboration or conflict.

The purpose is not to create a predictive model of behavior.  Rather the purpose of the simulation is to help scholars interested in policy change and theoretical development in the ACF by pinpointing theoretically uncertain areas of the framework for further discussion and elaboration.  The research also aims to adapt a tool traditionally used in business and manufacturing to improve the scholarship in policy process research. 

This initial attempt at using discrete event simulation does not utilize many of the strengths of this type of analysis tool (namely resource utilization, time between discrete steps, and queue time) and so is highly deterministic in nature. 

Discrete event simulations have been used to test out emergency management plans such as relief operations after an earthquake or the evacuation of a facility under varying evacuation policies (Cates,2005; Taafe et al., 2006).  Others have used discrete even simulation to design warehouses and customer service oriented organizations to reduce processing time and eliminate bottlenecks (Jurishica and Gallaher, 2006; Mazzuchi and Wallace, 2004). Our future aspirations of incorporating discrete event simulation into the public policy arena include resource allocation of city and non-profit resources to the public and understanding linkages between legislation, business, and individual users.

Project Team

 
Sam Gallaher (Lead researcher)
University of Colorado Denver
School of Public Affairs
Email: samuel.gallaher@ucdenver.edu

University of Colorado Denver
School of Public Affairs

Jon Pierce
University of Colorado Denver
School of Public Affairs
 
Uppsala University
Department of Government
 
University of Colorado Denver
School of Public Affairs

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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