Interactive Theory in economic decision making under uncertainty.

摘要

Traditional economic decision-making theories assume that human decision makers are rational agents. The first well-accepted normative model, the Expected Utility (EU) theory, provides a maximization principle guiding rational decision making (Schoemaker, 1982). The maximization tenet states that decision makers maximize expected utility. This principle of EU theory was first challenged by the Allais problem (Allais, 1953). The ensuing variants of EU models, either through adjusting probability and/or introducing psychological concepts, all aim at loosening stringent assumptions in the EU models, among which Prospect Theory (PT) is the most elaborate one.The separately proposed value function and weighting function in PT don't furnish us an adequate mechanism to explain these economic anomalies. Interactive Theory (IT), proposed here instead, offers non-multiplicative interactive explanation for economic decision-making. IT specifies that the value and the probability may not be interpreted independently or in an aggregate multiplicative form, in explaining choice preferences. The sensitivity of preferences is a function of the interaction between the value and the probability. The interpretation of one is conditional upon its value relative to the value of the other.This dissertation discusses two studies that show us the empirical evidence establishing such a non-multiplicative interaction between asset value and probability. The empirical evidence indicates that the outcome and the probability interact in a very specific pattern in the decision-making process, which can't be explained simply by the multiplicative rule of the EU models. The EU models can explain those results that are consistent with the maximization tenet, but fails for other results. PT does not offer us an adequately accurate value function and probability weighting function to explain those anomalies either. IT, however, offers a new insight in these types of phenomena, appealing to both the value and the probability at the same time and calling for a decision-making map in a multidimensional space to explain the choice preferences in a non-multiplicative, interactive way.