Bounded Rationality and Policy Approaches

Bounded rationality models and their closely related garbage can family of models have emerged as important ways of examining national policy-making when goals are not widely shared, attention is fleeting, time is scarce, choice is biased by framing effects, and collective benefits differ from individual interests. Under these conditions the utility of optimizing rationality is limited. Instead, Simon’s logic of bounded rationality stresses cognitive, computational, and organizational limitations in rational problem-solving while March and Olsen’s garbage cans and Kingdon’s multiple streams add the concepts of ambiguity and temporal sorting as fundamental steps in understanding how policies are made and legitimated. This chapter reviews their intellectual development, identifying their differences and similarities and specifying their benefits and drawbacks. The approaches supplement but do not supplant rationality. They remain fundamentally embedded within a broader information processing and interpreting view, indicating limitations and explaining deviations and pathologies. Both frameworks hypothesize robust processes that more closely match empirical observations of how policy is actually made, but doing so also complicates them substantially by increasing the amount of information needed to explain or predict public policies.

 

 

Bounded rationality models and their closely related garbage can family of models have emerged as important ways of examining national policy-making when goals are not widely shared, attention is fleeting, time is scarce, choice is biased by framing effects, and collective benefits differ from individual interests. Under these conditions the utility of optimizing rationality is limited. Instead, Simon’s logic of bounded rationality stresses cognitive, computational, and organizational limitations in rational problem-solving while March and Olsen’s garbage cans and Kingdon’s multiple streams add the concepts of ambiguity and temporal sorting as fundamental steps in understanding how policies are made and legitimated. This chapter reviews their intellectual development, identifying their differences and similarities and specifying their benefits and drawbacks. The approaches supplement but do not supplant rationality. They remain fundamentally embedded within a broader information processing and interpreting view, indicating limitations and explaining deviations and pathologies. Both frameworks hypothesize robust processes that more closely match empirical observations of how policy is actually made, but doing so also complicates them substantially by increasing the amount of information needed to explain or predict public policies.