Economics and psychology.Perfect rationality versus bounded rationality

Classical mathematical algorithms often fail to identify in time when the international financial crises occur although, as the classical theory of choice would suggest, the economic agents are rational and the markets are or should be efficient and behave also rationally. This contribution does not pretend to give a complete answer to these questions, but it will highlight some well-known limits of the classical theory of rational choice and compare this theory of choice with the approach that seeks to combine economics and psychology and that has established itself as cognitive or behavioral economics. In particular, the present paper will focus on the juxtaposition of the concepts of perfect rationality and bounded rationality. It concludes with some references to the literature of behavioral finance which has given important contributions in explaining the behavior and the anomalies of financial markets.Bounded rationality; procedural rationality; rational choice; cognitive economics

An experimental analysis of bounded rationality: Applying insights from behavioral economics to information systems

The paradigm of bounded rationality considers the limited ability of individuals to make consistent and rational choices. Due to the scarcity of research on this phenomenon in information systems, we conducted an experimental study investigating decision-making regarding risk preferences and social preferences. Moreover, we explored the stability of these preferences under different conditions and uncovered the role of information retrieval in individual decision-making. We find that although individuals are generally risk-averse and egoistic, none of these preferences is stable under the conditions tested which provides indices of boundedly rational decision-making. Although the information retrieved by participants generally allows to infer their preferences, the increasing amount and complexity of this information again often results in boundedly rational behavior.bounded rationality, experimental design, information retrieval, stability of attitudes and behavior, cognitive tracing, behavioral economics, behavioral information systems

Behavioural Anomalies, Bounded Rationality and Simple Heuristics

The use of bounded rationality in explaining economic phenomena has attracted growing attention. In spite of this, there is still considerable disagreement regarding the meaning of bounded rationality. Basov (2005) argues that when modeling boundedly rational behaviour it is desirable to start with an explicit formulation of the learning process. A complete understanding of the boundedly rational decision-making process requires development of an evolutionary-dynamic model which can give rise to such learning processes. Evolutionary dynamics implies that individuals use heuristics to adjust their choices in light of past experiences, moving in the direction that appears most beneficial, where these adjustment rules are assumed ‘hardwired’ into human cognition through the process of biological evolution. In this paper we elaborate on the latter point by building a model of evolutionary selection relevant to heuristics. We show that in addition to explaining the origin of learning rules this approach also sheds light on some well documented preference anomalies.Bounded Rationality;Heuristics;Replicator Dynamics

Behavioural Economics: Classical and Modern

In this paper, the origins and development of behavioural economics, beginning with the pioneering works of Herbert Simon (1953) and Ward Edwards (1954), is traced, described and (critically) discussed, in some detail. Two kinds of behavioural economics – classical and modern – are attributed, respectively, to the two pioneers. The mathematical foundations of classical behavioural economics is identified, largely, to be in the theory of computation and computational complexity; the corresponding mathematical basis for modern behavioural economics is, on the other hand, claimed to be a notion of subjective probability (at least at its origins in the works of Ward Edwards). The economic theories of behavior, challenging various aspects of 'orthodox' theory, were decisively influenced by these two mathematical underpinnings of the two theoriesClassical Behavioural Economics, Modern Behavioural Economics, Subjective Probability, Model of Computation, Computational Complexity. Subjective Expected Utility

Thinking Ahead: The Decision Problem

We propose a model of bounded rationality based on time-costs of deliberating current and future decisions. We model an individual decision maker%u2019s thinking process as a thought-experiment that takes time and let the decision maker %u201Cthink ahead%u201D about future decision problems in yet unrealized states of nature. By formulating an intertemporal, state-contingent, planning problem, which may involve costly deliberation in every state of nature, and by letting the decision-maker deliberate ahead of the realization of a state, we attempt to capture the basic idea that individuals generally do not think through a complete action-plan. Instead, individuals prioritize their thinking and leave deliberations on less important decisions to the time or event when they arise.

Entrepreneurial orientation and international performance: the moderating effect of decision-making rationality

This research examines how entrepreneurial orientation (EO) influences international performance (IP) of the firm taking into account the moderating effect of decision-making rationality (DR) on the EO–IP association. Such an investigation is significant because it considers the interplay of strategic decision-making processes supported by the bounded rationality concept in the entrepreneurship field. Drawing from a study on activities of 216 firms in the United States and United Kingdom, the evidence suggests that DR positively moderates the EO–IP association. The findings suggest that managers can improve IP by combining EO with rational (analytical) processes in their strategic decisions

A review of Multi-Agent Simulation Models in Agriculture

Multi-Agent Simulation (MAS) models are intended to capture emergent properties of complex systems that are not amenable to equilibrium analysis. They are beginning to see some use for analysing agricultural systems. The paper reports on work in progress to create a MAS for specific sectors in New Zealand agriculture. One part of the paper focuses on options for modelling land and other resources such as water, labour and capital in this model, as well as markets for exchanging resources and commodities. A second part considers options for modelling agent heterogeneity, especially risk preferences of farmers, and the impacts on decision-making. The final section outlines the MAS that the authors will be constructing over the next few years and the types of research questions that the model will help investigate.multi-agent simulation models, modelling, agent-based model, cellular automata, decision-making, Crop Production/Industries, Environmental Economics and Policy, Farm Management, Land Economics/Use, Livestock Production/Industries,

Fundamental Uncertainty, Portfolio Choice, and Liquidity Preference Theory

One of Keynes' core issues in his liquidity preference theory is how fundamental uncertainty affects the propensity to hold money as a liquid asset. The paper critically assesses various formal representations of fundamental uncertainty and provides an argument for a more boundedly rational approach to portfolio choice between liquidity and risky assets. The choice is made on the basis of individual beliefs which are subject to mental representations of the underlying economic structure. Self-consciousness arises when the agent is aware of the fact that beliefs are dispersed among agents due to the absence of a "true" model. Responding to this fact by increasing liquidity preference is rationalized by the higher ex post performance of choice. Moreover, we analyze the case that the portfolio is partially financed by debt. It is explored how fundamental uncertainty affects the volume of the portfolio and hence money and credit demand as well as the probability of debt failures.liquidity preference, portfolio choice, self-confidence, self-consciousness, fundamental uncertainty, bounded rationality, Keynes, Knight

A Conceptual Model of Investor Behavior

Based on a survey of behavioral finance literature, this paper presents a descriptive model of individual investor behavior in which investment decisions are seen as an iterative process of interactions between the investor and the investment environment. This investment process is influenced by a number of interdependent variables and driven by dual mental systems, the interplay of which contributes to boundedly rational behavior where investors use various heuristics and may exhibit behavioral biases. In the modeling tradition of cognitive science and intelligent systems, the investor is seen as a learning, adapting, and evolving entity that perceives the environment, processes information, acts upon it, and updates his or her internal states. This conceptual model can be used to build stylized representations of (classes of) individual investors, and further studied using the paradigm of agent-based artificial financial markets. By allowing us to implement individual investor behavior, to choose various market mechanisms, and to analyze the obtained asset prices, agent-based models can bridge the gap between the micro level of individual investor behavior and the macro level of aggregate market phenomena. It has been recognized, yet not fully explored, that these models could be used as a tool to generate or test various behavioral hypothesis.behavioral finance;financial decision making;agent-based artificial financial markets;cognitive modeling;investor behavior

Complexity and Bounded Rationality in Individual Decision Problems

I develop a model of endogenous bounded rationality due to search costs, arising implicitly from the decision problem's complexity. The decision maker is not required to know the entire structure of the problem when making choices. She can think ahead, through costly search, to reveal more of its details. However, the costs of search are not assumed exogenously; they are inferred from revealed preferences through choices. Thus, bounded rationality and its extent emerge endogenously: as problems become simpler or as the benefits of deeper search become larger relative to its costs, the choices more closely resemble those of a rational agent. For a fixed decision problem, the costs of search will vary across agents. For a given decision maker, they will vary across problems. The model explains, therefore, why the disparity, between observed choices and those prescribed under rationality, varies across agents and problems. It also suggests, under reasonable assumptions, an identifying prediction: a relation between the benefits of deeper search and the depth of the search. In decision problems with structure that allows the optimal foresight of search to be revealed from choices of plans of action, the relation can be tested on any agent-problem pair, rendering the model falsifiable. Moreover, the relation can be estimated allowing the model to make predictions with respect to how, in a given problem, changes in the terminal payoffs affect the depth of search and, consequently, choices. My approach provides a common framework for depicting the underlying limitations that force departures from rationality in different and unrelated decision-making situations. I show that it is consistent with violations of timing-independence in temporal framing problems, dynamic inconsistency and diversification bias in sequential versus simultaneous choice problems, and with plausible but contrasting risk attitudes across small- and large-stakes gambles.bounded rationality, complexity, search