🆚Game Theory and Economic Behavior Unit 13 – Behavioral Game Theory: Bounded Rationality

Key Concepts and Definitions

• Bounded rationality recognizes that decision-makers have limited cognitive abilities and information, leading to satisficing rather than optimizing behavior
  • Satisficing involves making decisions that are good enough, not necessarily optimal
• Heuristics are mental shortcuts or rules of thumb used to simplify complex decisions (availability heuristic, representativeness heuristic)
• Biases, such as the confirmation bias and anchoring effect, systematically influence decision-making
• Adaptive behavior involves adjusting decisions based on feedback and learning from past experiences
• Procedural rationality focuses on the decision-making process itself, rather than just the outcomes
• Ecological rationality suggests that heuristics can be effective when matched to the right environment
• Aspiration levels are the minimum acceptable outcomes that decision-makers aim for, adjusting their strategies accordingly

Historical Context and Development

• Herbert Simon introduced the concept of bounded rationality in the 1950s, challenging the assumptions of perfect rationality in economics
• Simon's work on satisficing and heuristics laid the foundation for behavioral economics and decision theory
• Kahneman and Tversky's research on cognitive biases and prospect theory (1970s) further advanced the field
  • Prospect theory explains how people make decisions under risk, considering reference points and loss aversion
• Gerd Gigerenzer and the ABC Research Group developed the concept of ecological rationality and the adaptive toolbox (1990s)
• The integration of psychology and economics has led to the growth of behavioral game theory, examining how bounded rationality affects strategic interactions
• Recent work has focused on the role of emotions, social norms, and learning in decision-making

Bounded Rationality Explained

• Bounded rationality recognizes the limitations of human cognitive abilities, such as limited memory, attention, and computational capacity
• Decision-makers often lack complete information and face time and resource constraints, preventing them from finding optimal solutions
• Satisficing involves choosing the first satisfactory option rather than searching for the best possible outcome
  • Satisficing can be an efficient strategy when the costs of searching for the optimal solution outweigh the benefits
• Heuristics simplify decision-making by focusing on a subset of available information and ignoring complex calculations
  • While heuristics can lead to biases, they can also be effective in certain environments (ecological rationality)
• Bounded rationality helps explain deviations from perfect rationality observed in real-world decision-making
• The concept has been applied to various domains, including consumer behavior, organizational decision-making, and policy-making

Models and Frameworks

• The Adaptive Toolbox (Gigerenzer) consists of fast and frugal heuristics that exploit the structure of the environment to make effective decisions
  • Examples include the recognition heuristic, take-the-best heuristic, and the 1/N rule for resource allocation
• The Aspiration Adaptation Theory (Selten) models how decision-makers adjust their aspiration levels based on past experiences and social comparisons
• The Rational Inattention model (Sims) suggests that decision-makers allocate their limited attention optimally, focusing on the most relevant information
• The Drift-Diffusion Model (Ratcliff) describes the accumulation of evidence over time in binary choice tasks, accounting for response times and accuracy
• The Entropy model of uncertainty (Shackle) measures the degree of surprise associated with different outcomes, influencing decision-making under uncertainty
• The Adaptive Markets Hypothesis (Lo) proposes that market efficiency evolves over time as participants adapt to changing conditions

Applications in Economics

• Bounded rationality has been applied to various areas of economics, including consumer behavior, financial decision-making, and macroeconomic policy
• In consumer behavior, bounded rationality explains phenomena such as brand loyalty, limited search, and the use of price as a quality signal
• In financial markets, bounded rationality can lead to herding behavior, asset bubbles, and the underreaction or overreaction to news
  • Behavioral finance incorporates insights from psychology to explain market anomalies and investor behavior
• In macroeconomics, bounded rationality has been used to model expectations formation, learning, and the effectiveness of monetary policy
  • The concept of rational inattention has been applied to understand the transmission of monetary policy and the persistence of economic shocks
• Bounded rationality has implications for policy-making, suggesting the need for choice architecture and nudges to guide decision-making

Experimental Evidence

• Experimental studies have provided evidence for the existence of bounded rationality and the use of heuristics in decision-making
• The Allais Paradox and the Ellsberg Paradox demonstrate violations of expected utility theory, a cornerstone of perfect rationality
• Studies on the conjunction fallacy and base rate neglect show how people deviate from probabilistic reasoning
• Experiments on anchoring and adjustment reveal the influence of irrelevant information on numerical estimates
• Research on the endowment effect and loss aversion supports the predictions of prospect theory
• Studies on the recognition heuristic and take-the-best heuristic provide evidence for the effectiveness of simple decision rules in certain environments
• Experiments on social preferences, such as ultimatum and dictator games, highlight the role of fairness and reciprocity in decision-making

Critiques and Limitations

• Some argue that bounded rationality is too vague and lacks a unified theoretical framework, making it difficult to derive testable predictions
• The concept of satisficing has been criticized for not specifying how decision-makers set their aspiration levels or when they stop searching for alternatives
• The ecological rationality approach has been questioned for its reliance on specific environmental structures and the difficulty of generalizing findings across contexts
• Critics argue that heuristics and biases are often identified post-hoc, without a clear understanding of their underlying mechanisms or boundary conditions
• There is debate about the extent to which bounded rationality reflects inherent cognitive limitations versus adaptive responses to complex environments
• Some researchers emphasize the importance of individual differences in cognitive abilities and decision-making styles, which may not be captured by general models of bounded rationality

Real-World Examples

• In consumer behavior, people often rely on brand recognition and satisficing when making purchasing decisions, rather than conducting extensive research (buying a familiar toothpaste brand)
• In financial markets, investors may exhibit herding behavior and rely on simple heuristics, such as the 1/N rule for asset allocation, leading to suboptimal portfolios
• In organizational decision-making, managers often use simple rules of thumb, such as the recognition heuristic, to make hiring or investment decisions under time pressure
• In medical decision-making, doctors may rely on heuristics, such as the availability heuristic, when diagnosing patients, potentially leading to biases and errors (overestimating the likelihood of a rare disease)
• In political decision-making, voters may use heuristics, such as party affiliation or candidate appearance, to simplify their choices, rather than evaluating all available information
• In environmental policy, bounded rationality can lead to the use of simple decision rules, such as the precautionary principle, when dealing with complex and uncertain risks (regulating new technologies)