RISK
RISK-SENSITIVE POLICY MAKING FOR POPULATIONS
RISK was a four-year project funded by the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no 618853. It started in 2013 and concluded at the end of2017.
The fundamental goal of RISK was to produce a unified theory of risk-sensitive policy making for populations with applications to various individual, medical, and governmental decision-making situations. Applications of particular interest included governmental decisions regarding social welfare such as taxes, demographic planning, education, health services, and criminal justice schemes, countermeasures against natural and man-made disasters, regulations to assure sustainable use of natural resources, and medical decisions including treatment of diseases and management of epidemics. The project relied on the use of mathematical tools from operations research, statistics, and economics to formulate risk-sensitive policy making problems involving individuals, to obtain efficient computational algorithms for these problems, and to gain insights into the effects of varying risk posture.
Mathematical formulation of dynamic population decision problems is an important step towards systematizing policy making and eliminating arbitrariness in adopted policies. In doing this, the choice of performance criteria against which to benchmark available alternatives is essential. Equally important is the determination of the relationships between individuals involved in the model, i.e., whether they compete against each other or cooperate, whether their actions are correlated in any way or not. Interactions between individuals determine the nature of the problem, the solution methodologies, and the complexity. Accordingly, theoretical models involved in the project can be categorized as optimization models, involving a single authority that determines an optimal policy for the entire population, and game-theoretic models, allowing individuals to pursue their own objectives when faced with different decision alternatives. For both categories, the fundamental goal was to elicit the impact of adopting various probabilistic criteria like expected value, expected utility, and mean-variance criteria. The objectives of RISK were:
Objective 1: To develop a unified theory of risk management for populations,
Objective 2: To apply the theory to public policy making.
The first two-year period of the project attacked Objective 1. Accordingly, existing population models are reviewed and their appropriateness for various population types are evaluated. Optimization models under optimality criteria including expected return, risk-averse utility, and extinction probability are set for various multi-type branching processes. The existence and the characterization of optimal policies are explored. Risk-sensitive criteria are also employed in several game-theoretic models that arise in the formulation of several societal problems. For the models investigated, the policies obtained from optimization and game-theoretic models are compared.
The second part of the project considered the implementation of this theory in the following application arenas: (1) regulations concerning social welfare (specifically, taxation, health services, educational benefits, and criminal justice systems), (2) control of natural resources, (3) countermeasures against natural and man-made disasters, and (4) management of epidemic diseases.