Interaction is the domain of economics where multiple decision-makers affect one another’s outcomes. It studies how individual choices collide, coordinate, or conflict through markets, strategic behavior, and institutional rules. Prices, allocations, and incentives emerge from these mutual dependencies—not from any single agent’s optimization. Choice ends where an agent can act alone; Interaction begins the moment one agent’s best response depends on another’s behavior. Interaction remains distinct from Aggregation & Dynamics, which analyzes system-wide outcomes over time rather than the strategic structure within which agents meet.
1. Domain Layer
This layer specifies what Interaction is allowed to analyze: how multiple decision-makers coordinate, compete, or strategize through prices, markets, institutions, and allocation mechanisms.
It defines the boundaries of multi-agent environments where outcomes arise from strategic behavior, bargaining, market structure, information flow, and institutional rules. The unit of analysis is no longer an isolated chooser but a system of interacting agents whose choices affect one another.
2. Evidence Layer
Here the focus shifts to what can be observed in practice: behavioral and statistical patterns emerging from markets, games, auctions, pricing, matching, and institutional interactions.
Evidence comes from bids, posted prices, market volumes, elasticities, competitive responses, information asymmetries, experimental markets, contract performance, and natural experiments that reveal how interaction shapes outcomes.
3. Structural Layer
This layer describes the internal mechanics that generate interactive outcomes: the strategic structures, equilibrium concepts, incentives, information flows, and institutional constraints governing multi-agent systems.
It includes supply and demand mechanisms, Nash equilibrium, game forms, price formation, externalities, incentive compatibility, market power, bargaining solutions, and general equilibrium structures linking markets together.
4. Method Layer
This section defines how the domain is interrogated and validated: experiments, mechanism design proofs, identification of strategic responses, structural estimation of games, and comparative-static analysis of equilibrium behavior.
It establishes how Interaction is tested through laboratory experiments, field experiments, auction data, contract outcomes, and equilibrium predictions, and how models are disciplined through counterfactual design and incentive-theoretic validation.
| Social Sciences | ||||
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| Economics | ||||
| Element | Scope Category | Sub-Item | Definition | Interaction (Markets, Strategy & Mechanisms) |
| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Studies how multiple agents interact, coordinate, compete, or strategize through markets, prices, institutions, contracts, and mechanism design. Includes supply–demand, price formation, market power, Nash equilibrium, incentives, auctions, matching markets, externalities, public goods, bargaining, contracts, information asymmetry, and general equilibrium. Excludes individual decision-making in isolation (pure micro choice) and excludes aggregate macro behavior unless emerging from interaction structure. |
| Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates at the level of multi-agent systems: markets, networks, institutions, and strategic environments. Interactions occur simultaneously or dynamically over time, ranging from bilateral bargaining to large decentralized markets and engineered mechanism platforms. | ||
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Agents, firms, goods, prices, quantities, payoff functions, beliefs, strategies, market institutions, contracts, signals, types (in asymmetric information models), mechanisms, allocation rules, matching objects (students–schools, workers–firms), equilibria. | |
| Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Strategic rationality; incentive compatibility; dominance; best-response structure; equilibrium existence; stability; efficiency; information conditions; externalities; complementarities or substitutability; market thickness; coordination properties; monotonicity in mechanism outcomes. | ||
| Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Market types (perfect competition, monopoly, oligopoly); game forms (normal form, extensive form); equilibrium types (Nash, subgame perfect, Bayesian Nash, Walrasian, correlated); mechanisms (auctions, matching, bargaining protocols, voting rules); environments (complete vs incomplete information). | ||
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Price vectors; quantity vectors; strategy profiles; beliefs over types; payoff values; marginal costs; valuations in auctions; probabilities of strategic states; allocation rules; equilibrium actions; private information signals; contract parameters. | |
| Parameterization | How variables encode and represent the system’s state. | Encoded via payoff matrices/functions, cost/production curves, valuation distributions, information structures, strategy spaces, mechanism rules (message spaces, allocation/payment functions), market supply/demand curves, belief hierarchies, and equilibrium mappings. | ||
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Perfect rationality and common knowledge of rationality; frictionless markets; complete information; price-taking behavior; convexity of preferences and technologies; quasilinear utilities in mechanism design; static equilibrium in dynamic environments; no transaction costs; risk neutrality in auctions. | |
| Validity Conditions | The limits and contexts in which idealizations hold or break down. | Fail under bounded rationality, behavioral biases, incomplete information, liquidity frictions, network effects, non-convexities, coordination failures, thin markets, complementarities, collusion, repeated interaction with path dependence, institutional rigidities. | ||
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Agents optimize strategically; markets clear or equilibrate through price or quantity adjustment; mechanisms map messages to allocations/payments predictably; equilibria exist under mild conditions; institutions impose structured constraints; beliefs update consistently in Bayesian settings. | |
| Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes agents understand strategic structure; assumes communication or signaling rules are well-defined; assumes institutions function reliably; assumes equilibrium is meaningful and stable; assumes utility is transferable or comparable in mechanism design when needed; assumes prices encapsulate relevant information in competitive markets. | ||
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Incentive constraints must align with mechanism outcomes; equilibrium definitions must match strategy spaces; supply/demand relations must satisfy feasibility; beliefs must be consistent with equilibrium strategies; allocation mechanisms must obey monotonicity and implementability constraints; market-clearing and stability must not conflict with agent rationality. | |
| Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Requires harmony among incentives, strategies, information structures, institutional rules, market-clearing conditions, equilibrium definitions, and welfare criteria. Must be consistent with microeconomic and general equilibrium foundations. | ||
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Price changes; quantity traded; market-clearing outcomes; bidding behavior in auctions; strategic choices in games; coordination or miscoordination; market entry/exit; bargaining outcomes; matching results (e.g., stable matches); signaling and screening patterns; welfare changes; evidence of externalities or market failures. |
| Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Inability to observe private information or true valuations; limited observation of belief updates; unobservable mixed strategies; noisy or incomplete transaction data; difficulty identifying causal pathways in competitive markets; selection bias in observed matches; strategic obfuscation; inability to detect tacit collusion directly. | ||
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Prices, quantities, bids, payoffs, utilities (inferred), production costs, profits, wages, transaction counts, welfare metrics, surplus measures, probabilities of strategic types, market shares, match quality scores. | |
| Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | Market data feeds; transaction-level datasets; auction logs; game experiments; matching market clearinghouses; firm production data; labor-market registries; bidding platforms; surveys on beliefs; mechanism platform analytics; revealed-preference consistency tests. | ||
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Equilibrium defined by mutual best responses; market-clearing defined by equality of supply and demand; auction winner defined by mechanism rules; matching stability defined by absence of blocking pairs; incentive compatibility defined by alignment of truthful reporting with best response; efficiency defined via Pareto or surplus-maximizing criteria. | |
| Procedures | The explicit steps required to perform a measurement in a reproducible way. | Estimating supply/demand; computing equilibrium; analyzing bidding data; testing for strategic complementarities; estimating structural game models; running matching algorithms (Gale–Shapley); evaluating mechanism outcomes; conducting auction or bargaining experiments; computing welfare or surplus decompositions. | ||
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Structured collection of transaction data; controlled lab/field experiments for strategic interaction; auction-format experiments; randomized supply or demand shocks; consistent collection of wage/price/production data; standardized mechanism trial runs; equilibrium calibration exercises. | |
| Sampling | Rules determining which subset of the domain is measured and how representative it is. | Sampling market participants across demographics; sampling bids across auction runs; sampling matched pairs in markets (schools, labor); sampling firms by size or sector; sampling strategies in repeated games; sampling experiments across different mechanisms; drawing repeated measures of equilibrium outcomes under varying parameters. | ||
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Price–quantity matrices; bidding logs; payoff tables; strategy profiles; surplus/welfare estimates; matching outcomes; equilibrium predictions vs actual data; mechanism allocation/payment outcomes; production and cost datasets; game experiment transcripts. | |
| Resolution | The granularity or precision with which data is captured. | Determined by temporal granularity of transaction data; precision of bid/price reporting; availability of micro-level strategic data; number of repetitions in experiments; clarity of mechanism rules; granularity of market segmentation; accuracy of cost/valuation estimates. | ||
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Cross-validating market outcomes with theoretical equilibria; calibrating structural parameters using repeated auctions or games; checking stability of matching outcomes across preference reports; validating bidding models with revealed data; back-testing strategic predictions; benchmarking mechanism performance against known optimal designs. | |
| Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Measurement error in prices/bids; misreporting of preferences; omitted-variable bias in structural game models; noisy beliefs; limited strategy observability; equilibrium multiplicity; misclassification of mechanism incentives; endogeneity in market participation; behavioral deviations from predicted strategies. | ||
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Supply–demand equilibrium laws; best-response dynamics; Nash-equilibrium fixed-point conditions; incentive-compatibility constraints; comparative-statics laws under shifting prices/technologies; matching stability conditions; auction revenue equivalence; mechanism monotonicity; competitive-market price-taking behavior; adverse-selection and moral-hazard patterns. |
| Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Equilibrium allocations; strategic best-response structure; dominance relationships; payoff ordering; incentive constraints; stable matchings; competitive price vectors; welfare theorems’ efficiency properties; distributional invariants of mechanisms (truthfulness, individual rationality). | ||
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Prices transmitting information; strategic best responses shaping outcomes; incentive design channeling private information into truthful revelation; auctions mapping bids into allocations/payments; matching algorithms producing stable outcomes; contracts shaping effort under hidden action; repeated interaction generating cooperation or punishment; market thickness amplifying matching efficiency. | |
| Pathways | Organized sequences of interactions forming a causal chain or network. | Beliefs → strategies → equilibrium → allocation; Valuations → bids → mechanism rules → outcomes; Preferences → demand/supply → price adjustment → market clearing; Information asymmetry → signaling/screening → separating or pooling equilibrium; Matching preferences → deferred acceptance → stable match; Dynamic incentives → continuation payoffs → long-run cooperation/defection. | ||
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Best response, Nash equilibrium, dominant strategy, Bayesian updating, incentive compatibility (IC), individual rationality (IR), mechanism, allocation rule, payment rule, matching, auction format, externality, market clearing, adverse selection, moral hazard, contract, signaling, screening. | |
| Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Market types: competitive, monopoly, oligopoly, auctions, matching markets; Games: static, dynamic, Bayesian, repeated; Mechanisms: direct, indirect, sealed-bid, ascending, VCG, deferred acceptance; Contracts: complete, incomplete, linear, nonlinear; Information structures: complete, incomplete, asymmetric; Externality structures: positive/negative, local/global. | ||
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Best-response: (s_i^(s_{-i}) = \arg\max u_i(s_i, s_{-i})); Nash: (s_i^ = s_i^(s_{-i}^)); Market clearing: (\sum_i x_i(p)=\sum_j y_j(p)); IC: (u_i(t_i, M(t_i)) \ge u_i(t_i, M(t_i’))); Auction payment rules; Matching stability constraints: no blocking pairs; Contract FOCs: marginal benefit = marginal cost; Belief updating: Bayes’ rule. | |
| Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Supply–demand diagrams; payoff matrices; extensive-form trees; auction allocation/payment charts; matching lattices; mechanism-direct revelation diagrams; Bayesian-type spaces; contract diagrams (effort vs incentives); general-equilibrium Edgeworth boxes; equilibrium graphs. | ||
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Perfect competition; fully rational agents; common knowledge of rationality; quasilinear utilities; symmetric auctions; independent private values; frictionless bargaining; fully transferable utility; static one-shot interactions; no transaction costs; complete contracts. | |
| Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Fail under behavioral biases; collusion; network effects; thick/thin-market frictions; liquidity/credit constraints; correlated values in auctions; incomplete contracts; multidimensional private information; dynamic path dependence; computational complexity preventing equilibrium computation; unraveling in matching markets. | ||
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Game theory as the spine of strategic interaction; mechanism design unifying incentives and information; general equilibrium unifying decentralized markets; auction theory linking valuation distributions and efficient allocation; matching theory linking preferences and stable outcomes; contract theory connecting incentives and behavior; welfare theorems connecting competitive outcomes to efficiency. | |
| Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Computer science (algorithmic mechanism design, complexity); political science (voting mechanisms, coalition formation); psychology (behavioral game theory); finance (market microstructure); operations research (matching, auctions, resource allocation); sociology (network effects); law (contract theory, incentives). | ||
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Randomizing prices or information treatments; designing auction/bidding experiments; varying mechanism rules (allocation/payment functions); altering matching rules; running strategic games with controlled payoffs; testing market thickness; manipulating contract terms; introducing shocks to supply/demand; assigning randomized types/signals in Bayesian games. |
| Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Gathering natural transaction data; observing unmanipulated bidding behavior; monitoring price adjustments; tracking equilibrium formation in real markets; observing stable vs unstable matching outcomes; studying natural bargaining interactions; documenting firm entry/exit; observing spontaneous coordination or failure in networks. | ||
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Testing Nash equilibrium predictions; verifying incentive compatibility; testing competitive-equilibrium conditions; checking for price-taking vs strategic pricing; validating revenue equivalence; testing matching stability; detecting adverse selection or moral hazard; evaluating mechanism performance (efficiency, fairness, truthfulness). | |
| Replication | The requirement that results be independently reproducible under similar conditions. | Re-running experiments under new populations or contexts; replicating auctions with alternative formats; repeating matching experiments with different preference distributions; recomputing equilibria on updated data; validating structural estimates using different identification strategies; replicating contract-performance tests with new cohorts. | ||
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Estimating structural game-theoretic parameters (values, costs, beliefs); evaluating equilibrium fit; quantifying deviations from Nash behavior; estimating welfare and surplus changes; analyzing bid shading; measuring stability of matches; estimating learning or belief-updating processes; identifying causal effects of incentives or mechanisms. | |
| Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Comparing auction formats (first-price, second-price, ascending, VCG); comparing market designs; testing Bayesian vs level-k or quantal-response models; comparing competitive vs oligopolistic pricing models; contrasting different matching mechanisms; evaluating contract structures (fixed vs incentive-based); comparing equilibrium refinements. | ||
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying misreporting of preferences; detecting collusion; separating noise from strategic deviation; distinguishing equilibrium multiplicity from estimation error; controlling for endogeneity in market participation; measuring strategic uncertainty; identifying misalignment between mechanism rules and agent understanding. | |
| Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Random assignment in experiments; using IVs for causal identification; controlling for selection in matching/migration; balancing observable covariates; preventing framing bias in strategic experiments; ensuring anonymity to limit social-preference contamination; pre-registering mechanisms and analysis plans. | ||
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Reviewing equilibrium derivations; checking IC/IR proofs; auditing mechanism-implementation correctness; validating structural estimation; challenging identification strategies; comparing predicted vs observed outcomes; re-evaluating welfare analyses; reconciling theory with behavioral anomalies. | |
| Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Updating mechanism designs after counterexamples; refining equilibrium concepts under bounded rationality; modifying contract models to include richer frictions; adjusting auction theory for correlated or interdependent values; incorporating behavioral or network effects; revising matching frameworks to address instability or strategic manipulation. | ||
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Disclosing mechanism rules, payoffs, randomization procedures, parameter values, identification strategies, estimation methods, equilibrium assumptions, and robustness tests; reporting failures or off-equilibrium behaviors; clarifying incentive structures and information. | |
| Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Protecting subjects in strategic experiments; avoiding manipulative mechanism deployment; honest reporting of non-convergence or unexpected strategic patterns; avoiding over-interpretation of thin data; ensuring replicability; acknowledging model limitations in complex markets. |