💰Psychology of Economic Decision-Making Unit 14 – Behavioral Game Theory in Decision-Making

Key Concepts and Foundations

• Game theory studies strategic interactions between rational decision-makers
• Assumes players are self-interested and aim to maximize their own payoffs
• Players make decisions based on available information and expectations of others' actions
• Foundational concepts include players, strategies, payoffs, and equilibria
  • Players are the individuals or entities making decisions in the game
  • Strategies are the possible actions or plans of action available to each player
  • Payoffs are the outcomes or rewards associated with each combination of strategies
  • Equilibria are the stable states where no player has an incentive to change their strategy
• Rationality assumes players have consistent preferences and make optimal decisions
• Common knowledge implies all players know the rules, strategies, and payoffs of the game
• Behavioral game theory incorporates insights from psychology and behavioral economics

Game Theory Basics

• Games can be classified as cooperative or non-cooperative based on players' ability to make binding agreements
• In cooperative games, players can form coalitions and make enforceable agreements
• Non-cooperative games involve players making independent decisions without binding agreements
• Games can be simultaneous or sequential depending on the timing of players' moves
  • Simultaneous games have players making decisions at the same time (Prisoner's Dilemma)
  • Sequential games have players making decisions in a specific order (Ultimatum Game)
• Payoff matrices represent the outcomes for each combination of strategies in a game
• Dominant strategies are the best responses regardless of the other player's actions
• Nash equilibrium is a set of strategies where no player can improve their payoff by unilaterally changing their strategy

Behavioral Aspects in Game Theory

• Behavioral game theory relaxes the assumptions of perfect rationality and self-interest
• Incorporates insights from psychology, such as bounded rationality, social preferences, and emotions
• Bounded rationality recognizes the cognitive limitations and biases in decision-making
  • Includes satisficing (choosing a satisfactory option rather than the optimal one)
  • Heuristics are mental shortcuts used to simplify complex decisions (availability heuristic)
• Social preferences account for concerns beyond self-interest, such as fairness, reciprocity, and altruism
  • Ultimatum Game demonstrates the role of fairness in decision-making
  • Dictator Game highlights altruistic behavior
• Emotions, such as anger, guilt, and empathy, can influence strategic decision-making
• Framing effects show how the presentation of information affects choices (loss aversion)
• Prospect theory explains decision-making under risk and uncertainty

Decision-Making Models

• Expected utility theory assumes players make decisions based on the probability-weighted average of payoffs
• Subjective expected utility theory incorporates individual beliefs and preferences
• Quantal response equilibrium allows for stochastic decision-making and errors
• Level-k thinking models players' reasoning about others' strategies
  • Level-0 players make random or naive choices
  • Level-1 players best respond to Level-0 players
  • Higher levels of reasoning involve best responding to lower levels
• Cognitive hierarchy theory extends level-k thinking by assuming a distribution of player types
• Experience-weighted attraction learning models players' learning and adaptation over time

Experimental Methods and Findings

• Experimental economics uses controlled experiments to test game-theoretic predictions
• Lab experiments provide a controlled environment to isolate specific factors
  • Ultimatum Game experiments reveal the importance of fairness considerations
  • Public Goods Game experiments study cooperation and free-riding behavior
• Field experiments apply game-theoretic concepts to real-world settings (auctions)
• Neuroeconomics combines neuroscience and economics to study the neural basis of decision-making
  • fMRI and EEG are used to measure brain activity during strategic interactions
• Experimental findings challenge assumptions of perfect rationality and self-interest
  • Observe deviations from Nash equilibrium predictions
  • Identify the role of social preferences, emotions, and bounded rationality

Real-World Applications

• Auction theory applies game theory to the design and analysis of auction mechanisms
  • Sealed-bid auctions (first-price, second-price) and open auctions (English, Dutch)
  • Revenue equivalence theorem states that under certain conditions, different auction formats yield the same expected revenue
• Matching markets use game-theoretic principles to match agents based on preferences
  • Stable matching ensures no two agents would prefer to be matched with each other over their current matches (college admissions, medical residency matching)
• Voting systems and social choice theory study the aggregation of individual preferences into collective decisions
  • Arrow's impossibility theorem highlights the challenges in designing fair voting systems
• Bargaining and negotiation models analyze the division of resources among players
  • Nash bargaining solution maximizes the product of players' gains relative to their disagreement payoffs
• Evolutionary game theory studies the dynamics of strategy adoption in populations
  • Replicator dynamics describe how strategies evolve based on their relative payoffs

Limitations and Criticisms

• Game theory assumes players have complete information about the game structure and payoffs
  • In reality, players often face uncertainty and incomplete information
• The assumption of perfect rationality is challenged by behavioral findings
  • Humans exhibit bounded rationality, cognitive biases, and emotional influences
• Game theory may oversimplify complex real-world situations
  • Ignores the role of communication, reputation, and social norms
• Experimental findings may not always generalize to real-world contexts
  • Lab experiments have controlled environments that may not capture real-world complexity
• Critics argue that game theory promotes a narrow view of human behavior
  • Focuses on self-interest and strategic reasoning, neglecting other motivations

Future Directions and Research

• Incorporating more realistic assumptions about human behavior and cognition
  • Developing models that account for bounded rationality, learning, and adaptation
• Studying the role of communication and language in strategic interactions
  • Analyzing how communication affects coordination, cooperation, and trust
• Investigating the impact of social norms, culture, and institutions on game-theoretic outcomes
  • Examining how cultural differences influence bargaining, cooperation, and competition
• Applying game theory to emerging domains, such as online platforms and social networks
  • Analyzing strategic interactions in online marketplaces, social media, and crowdsourcing
• Integrating game theory with other disciplines, such as computer science, biology, and political science
  • Developing interdisciplinary approaches to study complex systems and collective behavior
• Conducting large-scale field experiments to test game-theoretic predictions in real-world settings
  • Leveraging digital platforms and big data to study strategic behavior at scale
• Advancing the theoretical foundations of behavioral game theory
  • Developing axiomatic approaches and unifying frameworks for modeling bounded rationality and social preferences