Modeling Preparatory Commitment and Non-repeatable Decisions

Abstract

For many decisions with uncertain outcomes, prior preparation determines the payoffs received following choices. The payoff to an investment in human capital, for example, is a function of the ability to benefit from the course of training undertaken, and this ability is at least partly a function of one's self-regulated prior preparation. How should we use rational choice theory to model a goal-directed individual's preparatory commitment toward a consequential future decision if we cannot assume that preferences are fixed, that individuals engage in perfect information-processing, and that their expectations obey statistical decision theory? Introducing the concept of prefigurative commitment while invoking a stochastic decision tree for forecasts of future behavior, I show how a bounded rationality information-processing and evaluation mechanism generates courses of preparatory commitment decisions that differ from those that would result from strict adherence to orthodox decision theory. Throughout the development of the model, I discuss how the stochastic decision-tree framework can enhance sociological models of educational attainment.

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