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Modeling Preparatory Commitment and Non-repeatable Decisions

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  • Stephen L. Morgan

    (Department of Sociology, 366 Uris Hall, Cornell University, Ithaca, NY slm45@cornell.edu)

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.

Suggested Citation

  • Stephen L. Morgan, 2002. "Modeling Preparatory Commitment and Non-repeatable Decisions," Rationality and Society, , vol. 14(4), pages 387-429, November.
  • Handle: RePEc:sae:ratsoc:v:14:y:2002:i:4:p:387-429
    DOI: 10.1177/1043463102014004001
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    References listed on IDEAS

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    Cited by:

    1. Andros Kourtellos & Chih Ming Tan & Steven N. Durlauf, 2022. "The Great Gatsby Curve," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 571-605, August.
    2. Marina Lagemann & Peter Winker, 2022. "Inconsistent response behavior: A potential pitfall in modeling the link between educational attainment and social network characteristics," MAGKS Papers on Economics 202202, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Ehlert, Martin & Finger, Claudia & Rusconi, Alessandra & Solga, Heike, 2017. "Applying to college: Do information deficits lower the likelihood of college-eligible students from less-privileged families to pursue their college intentions?: Evidence from a field experiment," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 67, pages 193-212.
    4. Dirk Witteveen & Paul Attewell, 2022. "Black-White incentive inequality for college persistence," Rationality and Society, , vol. 34(2), pages 155-184, May.
    5. Sorokina, Olga V., 2008. "Credit Constraints in the Demand for Education: Evidence from Survey Data," MPRA Paper 11932, University Library of Munich, Germany.
    6. Stephen Vaisey, 2010. "What People Want: Rethinking Poverty, Culture, and Educational Attainment," The ANNALS of the American Academy of Political and Social Science, , vol. 629(1), pages 75-101, May.
    7. Dominik Becker, 2013. "The impact of teachers’ expectations on students’ educational opportunities in the life course: An empirical test of a subjective expected utility explanation," Rationality and Society, , vol. 25(4), pages 422-469, November.
    8. Mads Meier Jæger, 2007. "Economic and Social Returns To Educational Choices," Rationality and Society, , vol. 19(4), pages 451-483, November.
    9. Stephen L. Morgan, 2004. "Methodologist as Arbitrator," Sociological Methods & Research, , vol. 33(1), pages 3-53, August.

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