Presentation on theme: "Rational Choice Theory: A Forum for Exchange of Ideas between the Hard and Social Sciences in Predictive Behavioral Modeling Sun-Ki Chai Dept. of Sociology."— Presentation transcript:
Rational Choice Theory: A Forum for Exchange of Ideas between the Hard and Social Sciences in Predictive Behavioral Modeling Sun-Ki Chai Dept. of Sociology University of Hawai‘i
Unprecedented interest among “hard” scientists in study of human behavior Remarkably little use of existing social science theory or method, even those that adopt formal, positivist approaches Why? –Technical inadequacy? –Lack of familiarity? –Methodological incompatibility? The Social Sciences and Predictive Behavioral Modeling
ABCM is dominant approach to predictive behavioral modeling among computer scientists and engineers. Rational Choice is by far the dominant theoretical approach to predictive behavioral model in the social sciences. Until recently, the literatures developed without much dialogue or cross-citation. Social scientists have recently taken greater interest in ABCM. Still seen as alternative approaches rather than complements Agent-Based Computational Modeling and Rational Choice
subject to greater formal development and elaboration than any other approach applied to a much wider range of empirical behavioral phenomena spatiality, biology, and yes, culture, can be incorporated and indeed enhance rational choice models contrary to conventional wisdom, compatible with either analytic or computational solutions is both more general (in assumptions) and broader (in types of application) than conventional agent-based modeling Why is Rational Choice Theory Important to Hard Scientists?
both approaches take, often incompatible, multiple forms, however... like computational agent-based modeling, an individual- level approach that seeks to predict system-level outcomes through complex processes of aggregation (emergence as contested term) common roots in axiomatic models of behavior (Von Neumann/Morgenstern) game theory a formalization common to both approaches, though tends to be used differently Positive, Formal Rational Choice as One Type of Agent-Based Modeling?
Rational choice is used qualitatively as well as quantitatively –comparative historical rational choice –institutional rational choice –“folk psychology” Is used positive, normative, and interpretively –prescriptive models of justice and ethics –rational interpretation of personal narratives Qualitative Rational Choice as a Bridge to the Social Sciences and Humanities
Though based on common set of axioms, there is no one “single” rational choice model. “Thin” version includes: –logically consistent beliefs that do not violate laws of probability –“well-behaved” utility – strict order, completeness, asymmetry, and transitivity –actors choosing in order to maximize utility given beliefs “Thick” version adds: –self-regarding, materialistic (money, power, health), isomorphic utility –information-based (observation and valid inference) beliefs, common knowledge of rationality Basic Assumptions of Rational Choice
Conventional Rationality-based approach: single model generalizable to multiple, even novel contexts theories can be cumulated into larger whole tends to produce falsifiable predictions (though often anomalous) Conventional Culture-based approach: sensitive to social differences and personal development deeper and more nuanced depiction of social process avoids predictive anomalies (because it avoids prediction) Introducing Culture into “Thin” Rational Choice
specifying dimensions of culture in general fashion retaining simplicity and analytical tractability formalizing in way that is compatible with choice- theoretic models of action across full-range of environments modeling cultural change algorithmically combining generality and predictive determinacy Main Steps and Hurdles to Integration Conventional cultural typologies, e.g. (modern vs. traditional, Hofstede and “comparative capitalisms”) tend to focus on first two points but do not provide general implication for behavior.
Development of a general, predictive model of cultural change Integration with choice-theoretical model of action Software implementation into decision- support and simulation environments Objectives
Representation of culture through grid- group framework Modeling of cultural change through coherence model Implementation in simulation and decision- support systems Approach
ABSTRACT DIMENSIONS Grid = extent to which social rules prescribe and restrict action Group = extent to which identity is directed towards others Widely used in Cult./Soc. Anthropology and Political Science: Douglas 1970, 1978; Douglas and Wildavsky 1982; Wildavsky et al. 1990. Adapted for choice-theoretic models in Chai and Wildavsky 1993; Chai and Swedlow 1998. Grid-Group Framework for Representation of Culture
More abstract than competing frameworks for representing cultural differences Operationalization methods straightforward and well-tested Works well as front-end to “thin” rational choice models of decision-making Fits with abstract dimensions of social organization found in social theories, e.g. regulation and integration Decomposes into four major cultural types individualist – low grid / low group fatalist – high grid / low group hierarchical – high grid / high group egalitarian – low grid / low group Attributes of Grid-Group Framework
Grid-Group Transformations within Defined Group Boundaries Groupness-transformed payoff: y i = ( j<>i g i x j ) + x i Gridness-transformed payoff: u i = y i (ord(a i = o i ) + (1 –h i ) ord(a i <> o i )) where g i and h i are group and grid coefficients for individual i, a i is her action, x j is untransformed payoff, and o i her specified operation under standard procedures.
Expected Regret: subjective probability-weighted difference between maximal utility possible in a particular state of the environment and the utility provided by a chosen set of actions Coherence: expected regret of zero PREFERENCE AND BELIEF ASSUMPTIONS OF MODEL Meta-optimization Environment constrains Beliefs No “Yogic Utility” Parametric form, but not parametric values, determined by exposure to social communication Forms considered in order of message prevalence of communications describing such forms, but parameter weightings can be accepted or rejected. c.f. Chai 2001. Concepts and Assumptions of Coherence Model
actors are engaged in a collective process of constructing their own identities this process is aimed at creating an individual and collective sense of self that is both positive and consistent preferences and beliefs are not mere precursors to action, but there is a mutually causative relationship between these entities Intuitions behind Model
Coherence (preference-based): adjustment of g, h to minimize d Expected Regret (single-period, individual form): d = s (u(s,a*(s)) – u(s,a))) p(s) ds where a*(s)=argmax a A u(s,a) a=argmax a A, s S s u(s,a) p(s) ds s states of the environment, a actions, u utility function, and p subjective probabilities
Means will become ends (functional autonomy of motives) iff there exists there exists perception of some state of environment where alternative actions superior Sour grapes / forbidden fruit effect caused by actions that are perceived to preserve / alter the status quo more than alternatives Wishful / unwishful thinking strongest when an individual adopts actions that are subject to more / less variation in comparison to alternatives Effects depend on and magnify in proportion to subjective probability and extent to which chosen action will be suboptimal Some non-intuitive implications of coherence model...
Mutual altruism will be generated in groups engaging in repeated collective action, particularly where public goods are generated more reliably than private goods Materialistic culture will be generated by clearly defined structures of mobility in which the relative returns to vocational choices is not circumstance-dependent Explicit ideologies will be adopted by groups whose members face incoherence with regards to a similar set of action choices. Some implications linking structure to culture
Risk seeking or aversion: x = f(w); f’’(w) > 0 f’’(w) < 0 implies risk aversion; f”(w) > 0 implies risk seeking “Subjective” material payoffs are not a linear function of the quantity of goods Time discounting: U = ∑ T δ t u Cumulative utility is a function of period-specific utilities multiplied by a “discount factor” representing devaluation of deferred utility “Cultural” implications built into conventional economic models