Policy and Complex Systems
d ) Tools to display and present alternative policies .
4 . Decision Support for Selecting Policy
Alternatives a ) Instruments to distinguish , categorize , and compare policies . b ) Tools to support participatory decision making . a ) Means of answering what-if scenarios . b ) Tools for tracking the behaviors and reactions toward policies , before policy implementation ( e . g ., gaming and simulation ). c ) Tools for testing extreme values and worst-case scenarios .
5 . Monitoring implemented policies After implementation , policies can be monitored and evaluated using the evaluation criteria identified in the second step of the cycle . The policy analyst requires : a ) Tools and methods to compare and illustrate the before-and-after situations in order to evaluate the effects of a policy . b ) Tools for tracking the behaviors and the reactions .
Besides the specific requirements mentioned above , data collection , data analysis , and research are the common requirements for every step of the process . For an effective policy , consultation is also essential throughout the policy analysis process ( Hodge and Davies 2006 ). There are different levels of consultation ; for some projects , public opinion is taken into consideration while for others , this may need to be more limited due to , for example , security reasons ( Althaus , Bridgman , and Davis 2007 ). Furthermore , for selecting any policy instruments , the time constraints that the policy analysts work under need to be considered ( Patton and Sawicki 1993 ).
Policy analysts use various tools in different phases of the policy analysis cycle ( e . g ., surveys , brainstorming , sensitivity analysis , institutional analysis , etc .) ( Patton and Sawicki 1993 ). It is common practice to select a combination of tools that complement each other for different policy cases . Computational tools are in particular frequently applied to cover more scenarios and possibilities than normally possible with non-computational tools ( e . g ., scenario writing ). In this research , we especially focus on the computational tools that are used for policy analysis . We will compare these tools and reflect on the benefits and limitations of each in order to identify areas for improvement .
4 . Computational Approaches for Policy Analysis
Different policy tools focus on different aspects of the policy analysis cycle . Given the importance of computational tools , we introduce the major approaches that are currently in use , namely : Neo-classical Equilibrium Modeling ( NEM ), Traditional Game Theory ( TGT ), System Dynamics ( SD ), Serious Gaming ( SG ), and Agent-based Modeling ( ABM ). We then discuss the benefits and drawbacks of each as a policy analysis tool .
Neo-classical Equilibrium Modeling
Neo-classical Equilibrium Modeling ( NEM ) is a frequently applied tool for market-related policy problems . NEM provides mathematical models of markets and has special focus on maximizing profit , competition , and income distributions in markets through supply and demand ( Jones 1965 ).
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