Choice (Microeconomic Foundations) – SAT – Evidence – Observables

1. Magnitude Observables

Within Choice, Magnitude observables are:

• Scalar
• Agent-specific
• Behaviorally revealed
• Non-relational
• Non-normative

If an observable:

• Requires another agent
• Refers to structure, information, constraint, or evaluation
• Aggregates across agents

→ it is not a magnitude observable in Choice.

Property Category	Property	Observable	Value Type	Value	Reference Domain	Measurement Context	Bounds / Admissible Range	Resolution / Precision	Normalization / Baseline	Aggregation Rule	Measurement Method / Instrument	Uncertainty / Error Characterization	Revision / Update Status	Source Type
Magnitude	Intensity of preference	Binary choice outcomes (A chosen over B)	Level	{A,B}	Single entity	Timepoint	{A,B}	1 choice	NULL	NULL	Experimental protocol	Error rate / noise	Final	Experimental
Magnitude	Intensity of preference	Choice frequencies across repeated trials	Density / Intensity	Count(A)/N	Single entity	Interval	[0,1]	1/N	N	Mean	Experimental protocol	Sampling variance	Final	Experimental
Magnitude	Intensity of preference	Switching points between options	Level	Threshold value	Single entity	Interval	Menu bounds	Menu step	NULL	NULL	Experimental protocol	Interval uncertainty	Final	Experimental
Magnitude	Intensity of preference	Indifference points	Level	Equality point	Single entity	Interval	Comparison bounds	Step size	NULL	NULL	Experimental protocol	Interval uncertainty	Final	Experimental
Magnitude	Intensity of preference	Reservation prices	Level	Price threshold	Single entity	Timepoint	≥ 0	Price step	NULL	NULL	Experimental protocol	Response variance	Final	Experimental
Magnitude	Intensity of preference	Willingness-to-pay	Level	Max payment	Single entity	Timepoint	≥ 0	Price step	NULL	NULL	Experimental protocol	Response variance	Final	Experimental
Magnitude	Intensity of preference	Willingness-to-accept	Level	Min compensation	Single entity	Timepoint	≥ 0	Price step	NULL	NULL	Experimental protocol	Response variance	Final	Experimental
Magnitude	Intensity of preference	Acceptance / rejection at given prices	Level	{0,1}	Single entity	Timepoint	{0,1}	1 decision	NULL	NULL	Experimental protocol	Error rate / noise	Final	Experimental
Magnitude	Intensity of preference	Bid amounts in auctions	Level	Bid value	Single entity	Timepoint	≥ 0	Price step	NULL	NULL	Experimental protocol	Bid variance	Final	Experimental
Magnitude	Intensity of preference	Choice probabilities (stochastic choice)	Density / Intensity	p(A)	Single entity	Interval	[0,1]	1/N	Sum=1	Mean	Experimental protocol	Sampling variance	Final	Experimental
Magnitude	Intensity of preference	Elasticity of choice with respect to price or attributes	Density / Intensity	Elasticity value	Single entity	Experimental condition	Unbounded (ℝ)	Finite difference step	NULL	NULL	Choice variation protocol	Estimation error	Final	Experimental
Magnitude	Intensity of preference	Revealed marginal rates of substitution	Density / Intensity	MRS value	Single entity	Experimental condition	Positive real values	Menu step size	NULL	NULL	Revealed-preference task	Interval uncertainty	Final	Experimental
Magnitude	Intensity of preference	Compensating variation (revealed)	Level	Compensation amount	Single entity	Experimental condition	≥ 0	Smallest price increment	NULL	NULL	Revealed-preference elicitation	Response variance	Final	Experimental
Magnitude	Intensity of preference	Equivalent variation (revealed)	Level	Compensation amount	Single entity	Experimental condition	≥ 0	Smallest price increment	NULL	NULL	Revealed-preference elicitation	Response variance	Final	Experimental
Magnitude	Intensity of preference	Delay tolerance thresholds (when preference strength trades off with time)	Level	Delay threshold	Single entity	Experimental condition	≥ 0	Time-step resolution	NULL	NULL	Time–choice tradeoff task	Interval uncertainty	Final	Experimental
Magnitude	Intensity of preference	Risk premia implied by lottery choices	Level	Risk premium value	Single entity	Experimental condition	ℝ (typically ≥ 0)	Smallest payoff difference	NULL	NULL	Lottery-choice protocol	Estimation error	Final	Experimental
Magnitude	Resource quantity	Income received	Period-total	Income amount	Single entity	Interval	≥ 0	Smallest currency increment	NULL	Sum	Administrative record	Reporting error	Final	Administrative
Magnitude	Resource quantity	Cash-on-hand	Level	Cash amount	Single entity	Timepoint	≥ 0	Smallest currency increment	NULL	NULL	Account balance observation	Measurement noise	Final	Administrative
Magnitude	Resource quantity	Wealth level	Level	Net worth value	Single entity	Timepoint	ℝ	Smallest currency increment	NULL	NULL	Balance-sheet construction	Valuation error	Final	Derived
Magnitude	Resource quantity	Asset balances	Level	Asset value	Single entity	Timepoint	≥ 0	Smallest currency increment	NULL	NULL	Account records	Reporting error	Final	Administrative
Magnitude	Resource quantity	Debt balances	Level	Debt amount	Single entity	Timepoint	≥ 0	Smallest currency increment	NULL	NULL	Account records	Reporting error	Final	Administrative
Magnitude	Resource quantity	Credit limits	Level	Credit limit value	Single entity	Timepoint	≥ 0	Smallest currency increment	NULL	NULL	Lender records	Reporting error	Final	Administrative
Magnitude	Resource quantity	Endowed quantities of goods	Level	Quantity endowed	Single entity	Experimental condition	≥ 0	Smallest quantity unit	NULL	NULL	Experimental assignment	Assignment error	Final	Experimental
Magnitude	Resource quantity	Initial endowments	Level	Endowment quantity	Single entity	Timepoint	≥ 0	Smallest quantity unit	NULL	NULL	Initial condition record	Recording error	Final	Experimental
Magnitude	Resource quantity	Time available per period	Period-total	Time amount	Single entity	Interval	≥ 0	Smallest time unit	NULL	NULL	Time-budget accounting	Reporting error	Final	Observational
Magnitude	Resource quantity	Hours available for work or action	Period-total	Time amount	Single entity	Interval	≥ 0	Smallest time unit	NULL	NULL	Time-budget accounting	Reporting error	Final	Observational
Magnitude	Resource quantity	Budget size	Level	Budget amount	Single entity	Timepoint	≥ 0	Smallest currency increment	NULL	NULL	Budget record	Recording error	Final	Administrative
Magnitude	Resource quantity	Allowances or transfers received	Period-total	Transfer amount	Single entity	Interval	≥ 0	Smallest currency increment	NULL	Sum	Administrative record	Reporting error	Final	Administrative
Magnitude	Resource quantity	Stored inventory owned by the agent	Level	Inventory quantity	Single entity	Timepoint	≥ 0	Smallest quantity unit	NULL	NULL	Inventory record	Counting error	Final	Administrative
Magnitude	Outcome magnitude	Quantity consumed	Period-total	Quantity amount	Single entity	Interval	≥ 0	Smallest quantity unit	NULL	Sum	Consumption record	Reporting error	Final	Observational
Magnitude	Outcome magnitude	Consumption bundles	Level	Bundle vector	Single entity	Timepoint	≥ 0 for all components	Smallest quantity unit per good	NULL	NULL	Consumption record	Reporting error	Final	Observational
Magnitude	Outcome magnitude	Monetary payoff received	Level	Payoff amount	Single entity	Timepoint	ℝ (typically ≥ 0)	Smallest currency increment	NULL	NULL	Payment record	Recording error	Final	Administrative
Magnitude	Outcome magnitude	Physical output produced	Period-total	Output quantity	Single entity	Interval	≥ 0	Smallest quantity unit	NULL	Sum	Production record	Measurement error	Final	Observational
Magnitude	Outcome magnitude	Units of goods obtained	Period-total	Quantity obtained	Single entity	Interval	≥ 0	Smallest quantity unit	NULL	Sum	Transaction record	Counting error	Final	Administrative
Magnitude	Outcome magnitude	Time delays realized	Level	Delay duration	Single entity	Timepoint	≥ 0	Smallest time unit	NULL	NULL	Experimental timing record	Timing error	Final	Experimental
Magnitude	Outcome magnitude	Duration of outcomes	Period-total	Duration amount	Single entity	Interval	≥ 0	Smallest time unit	NULL	Sum	Timing record	Timing error	Final	Observational
Magnitude	Outcome magnitude	Effort expended (proxied by hours, energy use)	Period-total	Effort amount	Single entity	Interval	≥ 0	Smallest proxy unit	NULL	Sum	Time / energy logging	Reporting error	Final	Observational
Magnitude	Outcome magnitude	Financial return realized	Period-total	Return amount	Single entity	Interval	ℝ	Smallest currency increment	NULL	Sum	Financial record	Valuation error	Final	Administrative
Magnitude	Outcome magnitude	Losses incurred	Period-total	Loss amount	Single entity	Interval	≥ 0	Smallest currency increment	NULL	Sum	Financial record	Reporting error	Final	Administrative
Magnitude	Outcome magnitude	Gains realized	Period-total	Gain amount	Single entity	Interval	≥ 0	Smallest currency increment	NULL	Sum	Financial record	Reporting error	Final	Administrative
Magnitude	Outcome magnitude	Payoff realizations from lotteries	Level	Realized payoff	Single entity	Timepoint	ℝ	Smallest payoff increment	NULL	NULL	Lottery outcome record	Random draw variance	Final	Experimental
Magnitude	Outcome magnitude	Consumption level after choice	Level	Consumption quantity	Single entity	Timepoint	≥ 0	Smallest quantity unit	NULL	NULL	Consumption record	Reporting error	Final	Observational
Magnitude	Outcome magnitude	Resource depletion amount	Period-total	Depleted quantity	Single entity	Interval	≥ 0	Smallest quantity unit	NULL	Sum	Resource accounting record	Measurement error	Final	Observational

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2. Structure Observables

Within Choice, Structure observables are:

• Relational, not scalar
• Internal to a single agent
• About arrangement, not amount
• Static at the moment of choice

If an observable:

• Evolves over time → Dynamics
• Involves another agent → Interaction
• Quantifies intensity → Magnitude
• Encodes uncertainty numerically → Information

→ it does not belong here.

Property Category	Property	Observable	Elements	Relations	Configuration / Pattern Type	Topology	Dimensionality	Symmetry / Invariants	Hierarchy / Nesting	Role Labels	Ordering / Sequence Rule	Embedding / Representation Space	Structural Constraints	Granularity Level
Structure	Preference ordering	Binary choice relations (A chosen over B)	Options {A,B}	Binary dominance relation	Pairwise relation	Two-node directed relation	1D (pairwise)	Antisymmetry	None	Preferred, non-preferred	Linear (pairwise)	Abstract choice set	Exactly one relation per pair	Micro
Structure	Preference ordering	Revealed preference relations	Options	Revealed dominance relations	Directed graph	Connectivity via revealed edges	n-dimensional	Transitivity (if present)	None	Dominant, dominated	Partial order	Abstract choice space	No self-loops	Micro
Structure	Preference ordering	Choice rankings over finite menus	Menu options	Ordering relations	Total or partial order	Chain or DAG	1D ordering	Order invariance under relabeling	None	Rank positions	Linear or partial order	Abstract ordering space	Completeness (if total)	Micro
Structure	Preference ordering	Pairwise comparison outcomes	Option pairs	Comparison relations	Set of pairwise relations	Disconnected or connected pairs	1D (per pair)	Antisymmetry	None	Winner, loser	Pairwise order	Abstract comparison space	One outcome per pair	Micro
Structure	Preference ordering	Cyclic vs acyclic choice patterns	Options	Cyclic dominance relations	Directed cycle or DAG	Cycles vs no-cycle connectivity	n-dimensional	Cycle presence / absence	None	Cycle member, terminal	Cyclic or acyclic	Graph representation space	Admissible cycle structure	Micro
Structure	Preference ordering	Violations or satisfaction of: WARP	Options	Pairwise revealed preference relations	Directed graph with consistency check	Presence/absence of 2-cycle	n-dimensional	Antisymmetry (required)	None	Preferred, violated	Partial order	Abstract revealed-preference graph	No mutual dominance allowed	Micro
Structure	Preference ordering	Violations or satisfaction of: GARP	Options	Indirect revealed preference relations	Directed graph with path consistency	Cycle detection in transitive closure	n-dimensional	Acyclicity (required)	None	Path-consistent, violating	Partial order	Abstract revealed-preference graph	No cycles in transitive closure	Micro
Structure	Preference ordering	Violations or satisfaction of: SARP	Options	Strict revealed preference relations	Strict directed graph	No directed cycles	n-dimensional	Strict acyclicity	None	Strictly preferred	Strict order	Abstract strict-preference graph	No weak ties or cycles	Micro
Structure	Preference ordering	Dominance relations	Options	Componentwise dominance relations	Partial order	DAG	n-dimensional	Transitivity, antisymmetry	None	Dominant, dominated	Partial order	Attribute-comparison space	No self-dominance	Micro
Structure	Preference ordering	Lexicographic choice patterns	Options, attributes	Priority-based comparison relations	Lexicographic order	Ordered layers	n-dimensional	Priority invariance	Layered	Primary, secondary, etc.	Hierarchical order	Attribute-priority space	Fixed priority sequence	Micro
Structure	Preference ordering	Tie / indifference observations	Options	Equivalence relations	Equivalence classes	Disjoint components	n-dimensional	Reflexivity, symmetry, transitivity	None	Indifferent elements	Unordered within class	Abstract choice space	Equivalence consistency	Micro
Structure	Preference ordering	Menu-dependent ranking stability	Options, menus	Ranking correspondence across menus	Menu-indexed orders	Cross-menu mapping	n-dimensional	Invariance under menu restriction (if present)	None	Stable, unstable	Conditional order	Menu-indexed ordering space	Consistency across overlapping menus	Micro
Structure	Preference ordering	Context-independent ordering behavior	Options	Ordering relations	Context-invariant order	Single connected order	n-dimensional	Order invariance across contexts	None	Ordered elements	Fixed order	Abstract ordering space	Same order across contexts	Micro
Structure	Preference ordering	Revealed weak vs strict preference distinctions	Options	Weak and strict relations	Layered partial order	Nested relations	n-dimensional	Weak–strict consistency	Layered	Weakly preferred, strictly preferred	Partial order with tiers	Abstract preference space	Strict ⊂ weak	Micro
Structure	Feasible set geometry	Budget sets	Feasible bundles	Feasibility relations	Convex set (typical)	Connected region	n-dimensional (goods space)	Convexity (if present)	None	Feasible, infeasible	Unordered	Commodity space	Boundary-defined admissibility	Micro
Structure	Feasible set geometry	Price vectors faced by the agent	Goods, prices	Association of goods to price coordinates	Vector configuration	Product topology	n-dimensional	Coordinate permutation invariance	None	Price coordinate	Unordered	Price space	Fixed dimensionality	Micro
Structure	Feasible set geometry	Opportunity frontiers	Feasible bundles	Boundary relations	Frontier surface	Boundary topology	n-dimensional	Boundary invariance	None	Boundary, interior	Unordered	Commodity space	Frontier admissibility	Micro
Structure	Feasible set geometry	Available action menus	Actions	Inclusion relations	Finite or infinite set	Discrete or connected	n-dimensional	Set invariance	None	Available, unavailable	Unordered	Action space	Membership admissibility	Micro
Structure	Feasible set geometry	Consumption possibility sets	Bundles	Feasibility relations	Set geometry	Connected region	n-dimensional	Feasibility invariance	None	Feasible, infeasible	Unordered	Commodity space	Set admissibility	Micro
Structure	Feasible set geometry	Discrete vs continuous choice sets	Options	Adjacency relations	Discrete set or continuum	Disconnected vs connected	n-dimensional	Topological class	None	Discrete, continuous	Unordered	Choice space	Cardinality restriction	Micro
Structure	Feasible set geometry	Corner solutions observed	Feasible bundles	Boundary membership relations	Extreme-point configuration	Vertex topology	n-dimensional	Boundary invariance	None	Corner, non-corner	Unordered	Commodity space	Extreme-point admissibility	Micro
Structure	Feasible set geometry	Interior solutions observed	Feasible bundles	Interior membership relations	Interior-point configuration	Open-set topology	n-dimensional	Interior invariance	None	Interior, boundary	Unordered	Commodity space	Interior admissibility	Micro
Structure	Feasible set geometry	Binding vs non-binding constraint realizations	Feasible sets, boundaries	Boundary contact relations	Boundary-touching classification	Boundary vs interior	n-dimensional	Contact invariance	None	Binding, non-binding	Unordered	Feasible-set geometry	Boundary contact requirement	Micro
Structure	Feasible set geometry	Changes in feasible sets after exogenous shocks	Feasible sets	Set-inclusion relations across states	Set expansion / contraction pattern	Nested-set topology	n-dimensional	Set-mapping invariance	Nested	Pre-shock, post-shock	Unordered	Commodity space	Admissible set transformation	Micro
Structure	Feasible set geometry	Availability / stock constraints	Goods, quantities	Availability relations	Bounded-set geometry	Truncated region	n-dimensional	Upper-bound invariance	None	Available, unavailable	Unordered	Commodity space	Upper-bound admissibility	Micro
Structure	Feasible set geometry	Menu expansion or contraction	Menus, options	Set-inclusion relations	Nested-set pattern	Inclusion topology	n-dimensional	Inclusion invariance	Nested	Expanded, contracted	Unordered	Menu space	Admissible membership	Micro
Structure	Feasible set geometry	Technological menus available to the agent	Technologies, actions	Feasibility relations	Feasible-action set	Connected or discrete	n-dimensional	Feasibility invariance	None	Available, unavailable	Unordered	Action/technology space	Technological admissibility	Micro
Structure	Information partition	Signals received before choice	Signals, states	Partition relations	Information partition	Disjoint cells	n-dimensional	Partition invariance	None	Signal cell	Unordered	Information space	Mutual exclusivity	Micro
Structure	Information partition	Timing of information arrival	Information stages	Precedence relations	Ordered stages	Linear order	1D (stage order)	Order invariance	Layered	Early, late	Fixed sequence	Temporal-stage space	Stage admissibility	Micro
Structure	Information partition	Information disclosure events	Messages, recipients	Disclosure relations	Event-partition structure	Event-node connectivity	n-dimensional	Disclosure invariance	None	Disclosed, undisclosed	Unordered	Information-event space	Disclosure admissibility	Micro
Structure	Information partition	Choice differences across information conditions	Choices, information conditions	Condition–choice correspondence	Condition-indexed mapping	Disjoint condition domains	n-dimensional	Mapping invariance	None	Condition-specific choice	Unordered	Condition–choice space	One choice per condition	Micro
Structure	Information partition	State-contingent actions	States, actions	State–action assignment	Contingency mapping	Partition-aligned mapping	n-dimensional	State-label invariance	None	Action per state	Unordered	State–action space	Exactly one action per state	Micro
Structure	Information partition	Observed inability to distinguish states (pooling behavior)	States	Equivalence relations	Coarsened partition	Merged cells	n-dimensional	Indistinguishability invariance	Nested	Pooled states	Unordered	Information partition space	Cell merging admissibility	Micro
Structure	Information partition	Observed state differentiation (separating behavior)	States	Distinct-cell relations	Refined partition	Fully separated cells	n-dimensional	Distinguishability invariance	Nested	Separate states	Unordered	Information partition space	One state per cell	Micro
Structure	Information partition	Menu choices conditional on signals	Menus, signals	Signal–menu correspondence	Signal-indexed menu mapping	Disjoint signal domains	n-dimensional	Signal-label invariance	None	Menu per signal	Unordered	Signal–menu space	One menu per signal	Micro
Structure	Information partition	Revelation vs concealment treatments	Information items, agents	Disclosure relations	Binary disclosure partition	Disjoint visible/hidden cells	n-dimensional	Disclosure-status invariance	None	Revealed, concealed	Unordered	Information space	Mutual exclusivity	Micro
Structure	Information partition	Coarse vs fine information environments	States	Partition refinement relations	Coarse–fine partition lattice	Nested partitions	n-dimensional	Refinement invariance	Nested	Coarse cell, fine cell	Unordered	State space	Admissible refinement	Micro
Structure	Information partition	Experimental information treatments	Treatments, signals	Assignment relations	Treatment–signal partition	Disjoint treatment cells	n-dimensional	Treatment-label invariance	None	Treatment group	Unordered	Experimental information space	One signal structure per treatment	Micro
Structure	Information partition	Attention-constrained menus (what is seen vs unseen)	Options	Visibility relations	Visibility partition	Seen/unseen cells	n-dimensional	Visibility-status invariance	None	Visible, hidden	Unordered	Perceptual choice space	Limited visibility admissibility	Micro

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3. Dynamics Observables

Every item listed:

• Is directly observable
• Involves only one agent
• Requires no formal representation
• Is temporal, not structural
• Is non-strategic

If something:

• Requires probabilities → Information
• Requires equations → Method
• Requires other agents → Interaction
• Collapses time → Structure

…it does not belong here.

SAT – Evidence – Observables – Dynamics – Choice (Microeconomic Foundations)

Property Category	Property	Observable	State Variable	Time Parameter	Rate / Rule of Change	Direction of Change	Trajectory / Path	Timescale	Regime / Stability Class	Initial Condition	Terminal / Attractor State	Lag / Inertia	Perturbation Sensitivity	Reversibility
Dynamics	Internal state evolution	Sequences of choices over time	Choice state	Discrete decision periods	Transition rule between choices	Bidirectional	State sequence	Decision-to-decision	Stable or switching	Initial choice	Recurrent or absorbing choice	Decision inertia	Local sensitivity to perturbations	Path-dependent
Dynamics	Internal state evolution	Consumption paths	Consumption level	Continuous or discrete time	Difference / update rule	Increasing, decreasing, or oscillatory	Time series	Short-to-medium term	Stable or cyclical	Initial consumption	Steady level or cycle	Adjustment lag	Local sensitivity	Reversible (approx.)
Dynamics	Internal state evolution	Asset accumulation or depletion over time	Asset level	Continuous or discrete time	Accumulation / depletion equation	Increasing or decreasing	Time series	Long-term	Stable or divergent	Initial asset stock	Steady state or boundary	Strong inertia	Low to moderate sensitivity	Partially irreversible
Dynamics	Internal state evolution	Savings vs spending trajectories	Savings share / spending level	Discrete periods	Budget update rule	Bidirectional	Path in savings–spending space	Medium-term	Stable or oscillatory	Initial allocation	Steady allocation	Adjustment lag	Moderate sensitivity	Path-dependent
Dynamics	Internal state evolution	State-contingent actions by the same agent	Action state	Event-indexed time	Contingent transition rule	Conditional	Branching state paths	Event-driven	Conditional regimes	Initial state	State-specific attractors	Conditional lag	High sensitivity to state changes	Path-dependent
Dynamics	Internal state evolution	Changes in chosen bundles across periods	Bundle choice state	Discrete periods	Transition rule between bundles	Bidirectional	Bundle sequence	Period-to-period	Switching or stable	Initial bundle	Recurrent bundle or cycle	Choice inertia	Local sensitivity	Path-dependent
Dynamics	Internal state evolution	Habit persistence in choices	Choice propensity state	Discrete periods	Reinforcement update rule	Directional persistence	Slowly evolving path	Long-term	Metastable	Initial habit state	Habitual steady state	High inertia	Low sensitivity	Partially irreversible
Dynamics	Internal state evolution	Switching behavior across time	Choice state	Discrete periods	Switching transition rule	Bidirectional	Alternating state path	Short-term	Unstable or switching	Initial choice	No fixed attractor	Low inertia	High sensitivity	Reversible
Dynamics	Internal state evolution	Path dependence in decisions	Decision state	Discrete or event-indexed	History-dependent update rule	Conditional	History-dependent path	Medium-to-long term	Multiple basins	Initial decision	Path-specific attractor	Strong inertia	Moderate sensitivity	Irreversible
Dynamics	Internal state evolution	Repeated selection of similar actions	Action choice state	Discrete periods	Persistence rule	Directional persistence	Clustered action path	Medium-term	Stable	Initial action	Recurrent action set	Moderate inertia	Low sensitivity	Partially reversible
Dynamics	Internal state evolution	Changes in effort supplied across periods	Effort level state	Discrete periods	Effort adjustment rule	Increasing or decreasing	Effort time series	Medium-term	Stable or oscillatory	Initial effort level	Steady effort level	Moderate inertia	Moderate sensitivity	Partially reversible
Dynamics	Internal state evolution	Inventory drawdown or buildup	Inventory level state	Discrete or continuous time	Accumulation / depletion rule	Increasing or decreasing	Inventory path	Medium-to-long term	Stable or boundary-constrained	Initial inventory level	Steady level or exhaustion	High inertia	Low sensitivity	Partially irreversible
Dynamics	Learning within the agent	Changes in choice behavior following own past outcomes	Choice policy state	Discrete periods	Outcome-based update rule	Directional adaptation	Adaptive path	Medium-term	Adaptive / metastable	Initial policy	Locally stable policy	Adjustment lag	Moderate sensitivity	Path-dependent
Dynamics	Learning within the agent	Reduced choice variability over time	Choice variability state	Discrete periods	Variance-reduction rule	Decreasing	Convergent path	Medium-term	Convergent	Initial variability	Low-variability state	High inertia	Low sensitivity	Irreversible
Dynamics	Learning within the agent	Increased consistency in repeated decisions	Consistency state	Discrete periods	Consistency reinforcement rule	Increasing	Convergent trajectory	Medium-term	Stable	Initial consistency	High-consistency attractor	High inertia	Low sensitivity	Partially reversible
Dynamics	Learning within the agent	Trial-and-error behavior	Action-selection state	Discrete trials	Error-correction update rule	Bidirectional	Irregular exploratory path	Short-term	Adaptive / switching	Initial action	Locally stable action	Low inertia	High sensitivity	Reversible
Dynamics	Learning within the agent	Exploration followed by exploitation	Exploration intensity state	Discrete periods	Decay-to-focus rule	Decreasing exploration	Two-phase trajectory	Medium-term	Phase-shifted	High-exploration start	Exploitative steady state	Moderate inertia	Moderate sensitivity	Partially irreversible
Dynamics	Learning within the agent	Abandonment of previously chosen options	Option-usage state	Discrete periods	Deactivation rule	Decreasing	Exit path	Medium-term	Absorbing (abandoned)	Initial option set	Reduced option set	High inertia	Low sensitivity	Irreversible
Dynamics	Learning within the agent	Adoption of previously unchosen options	Option-usage state	Discrete periods	Activation rule	Increasing	Entry path	Medium-term	Expansive	Initial option set	Expanded option set	Moderate inertia	Moderate sensitivity	Reversible
Dynamics	Learning within the agent	Response to realized payoffs	Choice policy state	Discrete periods	Payoff-conditioned update rule	Directional adaptation	Feedback-driven path	Medium-term	Adaptive	Initial policy	Locally stable policy	Adjustment lag	High sensitivity	Path-dependent
Dynamics	Learning within the agent	Adjustment after mistakes or losses	Choice policy state	Discrete periods	Error-driven update rule	Directional correction	Corrective path	Short-to-medium term	Adaptive	Initial policy	Locally stable policy	Moderate inertia	High sensitivity	Path-dependent
Dynamics	Learning within the agent	Performance improvement across repetitions	Performance state	Discrete trials	Incremental improvement rule	Increasing	Convergent trajectory	Medium-term	Convergent	Initial performance	Performance plateau	High inertia	Low sensitivity	Partially irreversible
Dynamics	Learning within the agent	Experience-dependent switching rates	Switching propensity state	Discrete periods	Experience-conditioned update rule	Increasing or decreasing	Adaptive switching path	Medium-term	Adaptive	Initial propensity	Experience-stable level	Moderate inertia	Moderate sensitivity	Path-dependent
Dynamics	Discounting / time preference	Choice between sooner vs later rewards	Temporal choice state	Event-indexed time	Intertemporal update rule	Conditional	Branching temporal path	Medium-term	Conditional	Initial temporal preference	Stable temporal pattern	Moderate inertia	High sensitivity	Partially reversible
Dynamics	Discounting / time preference	Delay acceptance or rejection	Delay tolerance state	Event-indexed time	Threshold-based update rule	Bidirectional	Threshold-crossing path	Medium-term	Switching	Initial tolerance	Accepted or rejected state	Low inertia	High sensitivity	Reversible
Dynamics	Discounting / time preference	Intertemporal consumption allocation	Consumption allocation state	Discrete periods	Intertemporal allocation update rule	Reallocation across periods	Allocation path	Medium-to-long term	Stable or adaptive	Initial allocation	Steady allocation pattern	Moderate inertia	Moderate sensitivity	Partially reversible
Dynamics	Discounting / time preference	Saving vs immediate consumption decisions	Saving propensity state	Discrete periods	Allocation-switching rule	Bidirectional	Alternating or convergent path	Medium-term	Switching or stable	Initial propensity	Dominant allocation mode	Moderate inertia	High sensitivity	Path-dependent
Dynamics	Discounting / time preference	Early vs delayed payoff selection	Temporal choice state	Event-indexed time	Choice-update rule	Conditional	Branching temporal path	Medium-term	Conditional	Initial temporal choice	Stable selection pattern	Low inertia	High sensitivity	Reversible
Dynamics	Discounting / time preference	Preference reversals over time	Temporal preference state	Discrete periods	Reversal-trigger rule	Directional switching	Non-monotonic path	Medium-term	Unstable / switching	Initial preference	No fixed attractor	Low inertia	High sensitivity	Reversible
Dynamics	Discounting / time preference	Procrastination behavior	Action deferral state	Event-indexed time	Delay-extension rule	Increasing delay	Deferral path	Medium-term	Metastable	Initial deferral	Absorbing deferral state	High inertia	Low sensitivity	Irreversible
Dynamics	Discounting / time preference	Waiting behavior	Waiting tolerance state	Event-indexed time	Tolerance update rule	Increasing or decreasing	Tolerance path	Medium-term	Stable or metastable	Initial tolerance	Stable waiting level	Moderate inertia	Moderate sensitivity	Partially reversible
Dynamics	Discounting / time preference	Drop-off rates as delay increases	Participation state	Continuous or discrete delay	Delay-dependent attrition rule	Decreasing participation	Monotone decay path	Short-to-medium term	Stable	Full participation	Absorbing drop-off	Low inertia	High sensitivity	Irreversible
Dynamics	Discounting / time preference	Front-loading vs back-loading of consumption	Consumption timing state	Discrete periods	Timing reallocation rule	Reallocation toward early or late	Timing-allocation path	Medium-term	Stable or switching	Initial timing pattern	Dominant timing pattern	Moderate inertia	Moderate sensitivity	Partially reversible
Dynamics	Discounting / time preference	Timing of effort exertion	Effort timing state	Event-indexed time	Timing-shift rule	Earlier or later effort	Effort-timing path	Short-to-medium term	Adaptive	Initial effort timing	Stable timing pattern	Low inertia	High sensitivity	Reversible
Dynamics	Discounting / time preference	Time-dependent switching points	Switching threshold state	Discrete periods	Threshold update rule	Directional shift	Moving-threshold path	Medium-term	Adaptive	Initial threshold	Stabilized threshold	Moderate inertia	Moderate sensitivity	Path-dependent

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4. Interaction Observables

Observable Set

There are no admissible observables.

• No interactions are observed
• No influence between agents is observed
• No strategic dependence is observed
• No feedback from others is observed
• No joint action is observed

Why the Observable Set Is Empty

An observable in Interaction would require:

• Another agent
• Mutual influence
• Strategic coupling
• Feedback loops
• Correlated decision-making

All of those violate the Choice domain axiom.

So the correct observable list is:

∅ (empty set)

Important Clarification (to prevent future drift)

• Observing prices does not imply interaction
  (prices are taken as given in Choice)
• Observing menus does not imply interaction
  (menus are constraints, not agents)
• Observing past outcomes does not imply interaction
  (internal history ≠ interdependence)

The moment an observable requires another decision-maker, it exits Choice and enters Interaction (Markets, Strategy & Mechanisms).

SAT – Evidence – Observables – Interaction – Choice (Microeconomic Foundations)

Property Category	Property	Observable	Source Entity	Target Entity	Directionality	Interaction Type	Coupling Strength	Sign / Polarity	Interaction Scope	Mediation Channel	Latency / Delay	Feedback Presence	Context Dependence	Stability of Interaction
Interaction	NONE (zero interdependence)	NONE (zero interdependence)

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5. Constraint Observables

Every item listed:

• Is directly observable
• Is agent-specific
• Is about limits, not preferences
• Does not require formal modeling
• Does not invoke other agents

If something:

• Requires mathematics → Method
• Requires tradeoff valuation → Evaluation
• Requires uncertainty → Information
• Requires another agent → Interaction

…it does not belong here.

SAT – Evidence – Observables – Constraint – Choice (Microeconomic Foundations)

Property Category	Property	Observable	Constrained Entity / Variable	Constraint Type	Forbidden States	Permitted Region	Boundary Definition	Binding Status	Universality / Scope	Constraint Origin	Hardness	Tolerance / Slack	Interaction with Other Constraints	Enforcement Condition
Constraint	Budget constraint	Prices faced by the agent	Purchase configurations	Boundary	Expenditures exceeding price schedule	Expenditures consistent with prices	Price–quantity inequality	Conditional	Context-specific	Institutional	Hard	None	Nested with income constraint	Transaction infeasibility
Constraint	Budget constraint	Income received	Consumption expenditure	Capacity	Spending beyond available income	Spending ≤ income	Income cap	Conditional	Context-specific	Institutional	Hard	None	Nested with prices and transfers	Accounting inconsistency
Constraint	Budget constraint	Transfers received	Available spending	Capacity	Spending excluding transfers	Spending including transfers	Transfer-adjusted income bound	Conditional	Context-specific	Institutional	Hard	None	Nested with income constraint	Accounting inconsistency
Constraint	Budget constraint	Taxes paid	Net disposable income	Boundary	Spending ignoring tax obligations	Post-tax spending set	Tax-adjusted income inequality	Conditional	Context-specific	Institutional	Hard	None	Nested with income and transfer constraints	Rule breach detection
Constraint	Budget constraint	Fees paid	Net expenditure capacity	Boundary	Spending ignoring mandatory fees	Fee-adjusted spending set	Fee-adjusted budget inequality	Conditional	Context-specific	Institutional	Hard	None	Nested with prices and taxes	Rule breach detection
Constraint	Budget constraint	Credit limits	Expenditure configuration	Capacity	Spending beyond credit ceiling	Spending ≤ credit limit	Credit ceiling inequality	Conditional	Context-specific	Institutional	Hard	None	Nested with income constraint	Accounting inconsistency
Constraint	Budget constraint	Cash-on-hand	Immediate spending actions	Capacity	Purchases exceeding available cash	Purchases ≤ cash-on-hand	Cash balance threshold	Conditional	Local	Institutional	Hard	None	Nested with price constraint	Transaction infeasibility
Constraint	Budget constraint	Binding vs non-binding budget outcomes (revealed)	Choice configurations	Admissibility	Choices outside feasible set	Choices within feasible set	Budget boundary contact	Conditional	Context-specific	Institutional	Hard	None	Combined with prices/income	Feasibility violation
Constraint	Budget constraint	Foregone options due to insufficient resources	Option availability	Exclusivity	Resource-infeasible options	Resource-feasible options	Budget exclusion boundary	Binding	Local	Institutional	Hard	None	Nested with budget set	Option infeasibility
Constraint	Budget constraint	Rejected choices due to lack of funds	Action selection	Admissibility	Actions requiring unavailable funds	Fund-feasible actions	Budget admissibility edge	Binding	Local	Institutional	Hard	None	Nested with cash and credit	Transaction rejection
Constraint	Budget constraint	Corner solutions caused by budget exhaustion	Choice configuration	Boundary	Interior choices beyond budget	Boundary-feasible choices	Budget exhaustion boundary	Binding	Context-specific	Institutional	Hard	None	Nested with price constraints	Feasibility violation
Constraint	Budget constraint	Partial purchases due to insufficient budget	Purchase action	Capacity	Full purchase beyond budget	Partial purchase within budget	Residual-budget threshold	Binding	Local	Institutional	Hard	Limited (discrete divisibility)	Nested with price and cash constraints	Transaction infeasibility
Constraint	Technological constraint	Actions available to the agent	Action set	Admissibility	Actions not supported by technology	Technologically feasible actions	Feasibility domain edge	Non-binding	Context-specific	Physical / Institutional	Hard	None	Independent or nested	Logical impossibility
Constraint	Technological constraint	Actions unavailable to the agent	Action set	Exclusivity	Technologically infeasible actions	Supported actions only	Feasibility exclusion boundary	Binding	Universal (given tech)	Physical / Institutional	Hard	None	Independent	Physical impossibility
Constraint	Technological constraint	Successful vs failed attempts	Action execution	Admissibility	Failed executions	Successful executions	Execution feasibility boundary	Conditional	Local	Physical	Hard	None	Nested with action availability	Execution failure detection
Constraint	Technological constraint	Maximum producible quantities	Output configuration	Capacity	Output beyond technical maximum	Output ≤ technical maximum	Capacity ceiling	Binding	Context-specific	Physical	Hard	None	Nested with input constraints	Physical impossibility
Constraint	Technological constraint	Conversion limits (inputs → outputs, observed)	Input–output mappings	Conservation	Output without required inputs	Technically feasible conversions	Conversion feasibility surface	Binding	Context-specific	Physical	Hard	None	Nested with input availability	Physical impossibility
Constraint	Technological constraint	Capability ceilings	Action performance state	Capacity	Actions exceeding capability	Capability-feasible actions	Capability threshold	Binding	Context-specific	Physical	Hard	None	Independent or nested	Physical impossibility
Constraint	Technological constraint	Discrete vs continuous action availability	Action space	Admissibility	Non-supported action forms	Supported discrete/continuous actions	Action-space topology edge	Non-binding	Context-specific	Physical / Logical	Hard	None	Independent	Logical inconsistency
Constraint	Technological constraint	Required inputs for outcomes (observed)	Outcome realization	Admissibility	Outcomes without prerequisite inputs	Input-supported outcomes	Input requirement boundary	Binding	Context-specific	Physical	Hard	None	Nested with budget and tech	Physical impossibility
Constraint	Technological constraint	Infeasible outcomes never realized	Outcome realizations	Admissibility	Technologically impossible outcomes	Technically feasible outcomes	Feasibility exclusion boundary	Binding	Universal (given technology)	Physical	Hard	None	Independent	Physical impossibility
Constraint	Technological constraint	Tool or method availability	Action execution	Admissibility	Actions requiring unavailable tools	Tool-supported actions	Tool-availability boundary	Binding	Context-specific	Physical / Institutional	Hard	None	Nested with capability constraints	Execution impossibility
Constraint	Time constraint	Time available per period	Action scheduling	Capacity	Actions exceeding time endowment	Time-feasible schedules	Time-budget ceiling	Binding	Universal (per period)	Physical	Hard	None	Nested with action constraints	Scheduling infeasibility
Constraint	Time constraint	Duration of actions	Action execution	Boundary	Actions exceeding allowable duration	Duration-feasible actions	Duration threshold	Conditional	Context-specific	Physical	Hard	Limited	Nested with deadlines	Timeout recognition
Constraint	Time constraint	Deadlines faced	Action completion	Boundary	Actions completed after deadline	On-time completions	Deadline cutoff	Binding	Context-specific	Institutional / Physical	Hard	None	Nested with duration and time budgets	Deadline violation
Constraint	Time constraint	Waiting times	Action initiation	Boundary	Initiation before waiting requirement	Initiation after required wait	Minimum-wait threshold	Conditional	Context-specific	Physical / Institutional	Hard	None	Nested with deadlines	Early-action detection
Constraint	Time constraint	Time spent on activities	Activity allocation	Capacity	Allocations exceeding time budget	Time-feasible allocations	Time-budget ceiling	Binding	Universal (per period)	Physical	Hard	None	Nested with action sequencing	Scheduling infeasibility
Constraint	Time constraint	Actions foregone due to lack of time	Action selection	Exclusivity	Actions requiring unavailable time	Time-feasible actions	Time-availability boundary	Binding	Local	Physical	Hard	None	Nested with time budget	Inability to schedule
Constraint	Time constraint	Sequencing imposed by time limits	Action order	Ordering	Orders violating time precedence	Time-consistent sequences	Precedence constraint	Binding	Context-specific	Physical / Institutional	Hard	None	Nested with duration constraints	Order violation
Constraint	Time constraint	Missed opportunities due to delay	Opportunity access	Boundary	Opportunities accessed after expiry	Timely access set	Opportunity-expiry cutoff	Binding	Context-specific	Institutional	Hard	None	Nested with waiting and deadlines	Expiry recognition
Constraint	Time constraint	Truncated actions caused by time limits	Action execution	Boundary	Completion beyond time limit	Partial or completed actions within limit	Time cutoff	Binding	Context-specific	Physical / Institutional	Hard	Limited	Nested with duration constraints	Timeout detection
Constraint	Time constraint	Horizon endpoints (last feasible period)	Action scheduling	Boundary	Actions initiated after horizon	Actions within horizon	Horizon endpoint	Binding	Context-specific	Institutional	Hard	None	Nested with time budget	Period-expiry recognition
Constraint	Physical or logical feasibility	Actions never taken because impossible	Action space	Admissibility	Physically or logically impossible actions	Feasible actions only	Feasibility exclusion boundary	Binding	Universal	Physical / Logical	Hard	None	Independent	Impossibility recognition
Constraint	Physical or logical feasibility	Attempted actions that fail	Action execution	Admissibility	Failed executions	Successful executions	Execution feasibility boundary	Conditional	Context-specific	Physical / Logical	Hard	None	Nested with capability constraints	Failure detection
Constraint	Physical or logical feasibility	Physical impossibility events	Outcome realization	Admissibility	Impossible outcomes	Physically realizable outcomes	Physical feasibility boundary	Binding	Universal	Physical	Hard	None	Independent	Physical impossibility detection
Constraint	Physical or logical feasibility	Logical exclusions (mutually exclusive actions)	Action combinations	Exclusivity	Joint execution of exclusive actions	Non-conflicting action sets	Mutual-exclusion boundary	Binding	Universal	Logical	Hard	None	Independent	Logical inconsistency
Constraint	Physical or logical feasibility	Hard prohibitions (cannot co-occur)	Action configurations	Prohibition	Prohibited co-occurring actions	Allowed configurations	Prohibition boundary	Binding	Universal	Institutional / Logical	Hard	None	Independent	Rule violation detection
Constraint	Physical or logical feasibility	Domain exclusions (action not in menu)	Action selection	Admissibility	Actions outside domain/menu	Menu-contained actions	Domain boundary	Binding	Context-specific	Logical / Institutional	Hard	None	Nested with menu constraints	Invalid-selection detection
Constraint	Physical or logical feasibility	Binary feasibility outcomes (possible / impossible)	Action feasibility state	Admissibility	Impossible actions	Possible actions	Feasibility partition	Binding	Universal	Physical / Logical	Hard	None	Independent	Feasibility check
Constraint	Physical or logical feasibility	Observed impossibility boundaries	State or action space	Boundary	States beyond feasible limit	Feasible region	Impossibility boundary	Binding	Universal	Physical / Logical	Hard	None	Independent	Boundary violation
Constraint	Physical or logical feasibility	Failed execution attempts	Action execution	Admissibility	Failed executions	Successful executions	Execution feasibility boundary	Conditional	Context-specific	Physical / Logical	Hard	None	Nested with capability constraints	Failure detection
Constraint	Physical or logical feasibility	Invalid action selections rejected by the environment	Action selection	Admissibility	Invalid selections	Valid selections	Validity boundary	Binding	Context-specific	Logical / Institutional	Hard	None	Nested with domain constraints	Rejection signal

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6. Information Observables

Every item listed:

• Is directly observable
• Refers to a single agent
• Requires no numerical belief representation
• Does not involve other agents
• Is informational, not evaluative

If something:

• Assigns numerical likelihoods → Method
• Optimizes over risk → Evaluation
• Evolves beliefs formally → Dynamics
• Requires another agent → Interaction

…it does not belong here.

SAT – Evidence – Observables – Information – Choice (Microeconomic Foundations)

Property Category	Property	Observable	Information Content	Carrier / Medium	Uncertainty	Resolution / Granularity	Signal vs Noise Distinction	Observability / Accessibility	Encoding Scheme	Update / Learning Rule	Predictive Power	Complexity Measure	Redundancy / Correlation	Definability / Expressibility
Information	Beliefs about states	Choices contingent on different realized states	State–action distinctions	Internal belief representation	Ambiguity over state realization	Discrete state distinctions	State signals vs irrelevant variation	Partially observable	State–action mapping	Evidence-conditioned revision	Predictive of action under state	Moderate description length	Correlated across states	Definable within state space
Information	Beliefs about states	State-contingent actions	Mapping from states to actions	Internal belief representation	Uncertainty over state identity	State-level granularity	State signal vs noise	Partially observable	Contingency mapping	Conditional updating	Predictive of chosen action	Moderate	Redundant across similar states	Definable
Information	Beliefs about states	Betting behavior	Subjective likelihood distinctions	Internal belief representation	Probabilistic uncertainty	Outcome-level granularity	Outcome signal vs randomness	Observable via choice	Probability encoding	Outcome-based update	Predictive of beliefs	Moderate	Correlated with related bets	Definable
Information	Beliefs about states	Insurance purchase or non-purchase	Loss-state likelihood distinctions	Internal belief representation	Risk uncertainty	Binary loss/no-loss	Loss signal vs background risk	Observable via choice	Binary threshold encoding	Experience-based update	Predictive of loss belief	Low	Correlated with other risk choices	Definable
Information	Beliefs about states	Portfolio allocation choices	Beliefs over return states	Internal belief representation	Distributional uncertainty	Asset-return granularity	Return signal vs noise	Observable via allocation	Distributional encoding	Performance-based update	Predictive of future allocation	High	Correlated across assets	Definable
Information	Beliefs about states	Acceptance or rejection under uncertainty	Accept/reject distinctions conditional on states	Internal belief representation	Outcome ambiguity	Binary outcome granularity	Outcome-relevant signal vs noise	Observable via choice	Binary decision encoding	Evidence-conditioned revision	Predictive of decision boundary	Low	Correlated with similar choices	Definable
Information	Beliefs about states	Conditional choices following signals	Signal–action distinctions	Internal belief representation	Signal uncertainty	Signal-level granularity	Signal vs irrelevant variation	Partially observable	Signal–action mapping	Signal-based updating	Predictive of response to signal	Moderate	Correlated across related signals	Definable
Information	Beliefs about states	Actions taken after information revelation	Pre/post information distinctions	Internal belief representation	Reduced post-revelation uncertainty	Event-level granularity	Informative event vs background	Observable via choice	Event-conditioned encoding	Revelation-based update	Predictive of post-event action	Moderate	Correlated across similar events	Definable
Information	Beliefs about states	Hedging behavior	Joint-state exposure distinctions	Internal belief representation	Distributional uncertainty	Multi-state granularity	Risk-relevant signal vs noise	Observable via allocation	Distributional encoding	Outcome-based updating	Predictive of variance exposure	High	Correlated across assets/states	Definable
Information	Beliefs about states	Safety-seeking choices	Downside-state distinctions	Internal belief representation	Loss-focused uncertainty	Coarse downside granularity	Downside signal vs background	Observable via choice	Threshold-based encoding	Experience-based update	Predictive of conservative actions	Low to moderate	Correlated with other safety choices	Definable
Information	Beliefs about states	Contingent contracts selected	State–payoff contingencies	Internal belief representation	State uncertainty	Contract-state granularity	Contract-relevant signal vs noise	Observable via choice	Contingency encoding	Evidence-conditioned revision	Predictive of state beliefs	Moderate	Correlated across contract choices	Definable
Information	Beliefs about states	Menu choices conditioned on uncertainty	Menu–uncertainty distinctions	Internal belief representation	Menu-level ambiguity	Menu-level granularity	Informative uncertainty vs noise	Observable via choice	Menu-selection encoding	Experience-based update	Predictive of uncertainty response	Moderate	Correlated across menus	Definable
Information	Information quality	Number of distinct signals received	Signal count distinctions	Signal medium / record	Signal uncertainty	Discrete signal granularity	Signal identification vs noise	Observable	Count-based encoding	Accumulation update	Predictive of information richness	Low	Potentially redundant signals	Definable
Information	Information quality	Timing of signal arrival	Signal timing distinctions	Signal medium / record	Temporal uncertainty	Event-time granularity	Timely signal vs delay noise	Observable	Temporal encoding	Time-conditioned update	Predictive of reaction timing	Low to moderate	Correlated across signals	Definable
Information	Information quality	Presence or absence of information	Information availability distinction	Signal medium	Binary uncertainty (known/unknown)	Binary granularity	Information vs absence	Observable / hidden	Binary availability encoding	Availability-based update	Predictive of action under ignorance	Low	Redundant across contexts	Definable
Information	Information quality	Delayed vs immediate information	Timing distinction of information availability	Signal medium / record	Temporal uncertainty	Event-time granularity	Timely signal vs delay noise	Observable	Temporal availability encoding	Time-conditioned update	Predictive of timing-sensitive choices	Low to moderate	Correlated across signals	Definable
Information	Information quality	Noisy vs clear signal realizations (as delivered)	Signal quality distinctions	Signal medium	Noise/ambiguity	Fine vs coarse signal granularity	Signal clarity vs noise characterization	Observable	Quality-weighted encoding	Noise-filtering update	Predictive of response accuracy	Moderate	Correlated across similar signals	Definable
Information	Information quality	Information disclosure events	Disclosure state distinctions	Communication medium	Uncertainty reduction	Event-level granularity	Disclosed content vs background	Observable	Event-flag encoding	Disclosure-based update	Predictive of post-disclosure behavior	Moderate	Redundant across channels	Definable
Information	Information quality	Menu changes caused by information release	Menu–information linkage distinctions	Decision interface	Conditional uncertainty	Menu-level granularity	Information-driven menu change vs noise	Observable	Conditional menu encoding	Revelation-conditioned update	Predictive of menu-dependent choice	Moderate	Correlated across releases	Definable
Information	Information quality	Differences in choice across information treatments	Treatment–choice distinctions	Experimental record	Treatment uncertainty	Treatment-level granularity	Treatment signal vs uncontrolled variation	Observable	Treatment-indexed encoding	Treatment-based update	Predictive of information effects	Moderate	Correlated within treatment groups	Definable
Information	Information quality	Observed confusion vs clarity responses	Confused vs clear informational states	Signal medium / presentation interface	Ambiguity level	Coarse vs fine distinctions	Clear signal vs ambiguous noise	Observable via response patterns	Clarity-coded encoding	Experience-conditioned revision	Predictive of response consistency	Low to moderate	Correlated across similar presentations	Definable
Information	Information quality	Attention-limited visibility of options	Visible vs unseen option distinctions	Decision interface	Partial observability	Option-level granularity	Attended signals vs unattended noise	Partially observable	Visibility-filtered encoding	Attention-updating rule	Predictive of option consideration	Moderate	Correlated across option sets	Definable
Information	Information quality	Withheld vs revealed attributes	Attribute availability distinctions	Information display medium	Attribute uncertainty	Attribute-level granularity	Revealed attributes vs hidden noise	Partially observable	Attribute-mask encoding	Revelation-conditioned update	Predictive of attribute-sensitive choice	Moderate	Correlated across attributes	Definable
Information	Perceived uncertainty	Risk-averse vs risk-seeking choice patterns	Perceived outcome spread distinctions	Internal belief representation	Perceived risk uncertainty	Distributional granularity	Risk-relevant signal vs background	Observable via choice	Distributional encoding	Experience-based update	Predictive of variance exposure	High	Correlated across risky choices	Definable
Information	Perceived uncertainty	Demand for certainty	Certainty vs uncertainty distinctions	Internal belief representation	Ambiguity aversion	Binary or coarse granularity	Certain outcomes vs ambiguous noise	Observable via choice	Certainty-preference encoding	Feedback-based update	Predictive of information-seeking	Low to moderate	Correlated with safety choices	Definable
Information	Perceived uncertainty	Preference for sure outcomes	Certain vs uncertain outcome distinctions	Internal belief representation	Low vs high perceived uncertainty	Binary or coarse outcome granularity	Certain signal vs uncertain noise	Observable via choice	Certainty-flag encoding	Experience-conditioned update	Predictive of safe-option selection	Low	Correlated with ambiguity avoidance	Definable
Information	Perceived uncertainty	Avoidance of ambiguous options	Ambiguous vs non-ambiguous option distinctions	Internal belief representation	Ambiguity uncertainty	Option-level granularity	Ambiguity signal vs background noise	Observable via choice	Ambiguity-coded encoding	Feedback-based update	Predictive of option exclusion	Moderate	Correlated across ambiguous options	Definable
Information	Perceived uncertainty	Option elimination under uncertainty	Feasible-option belief distinctions	Internal belief representation	Unresolved uncertainty	Menu-level granularity	Eliminated vs retained options	Observable via choice	Elimination-mask encoding	Uncertainty-driven update	Predictive of reduced consideration sets	Moderate	Correlated within menus	Definable
Information	Perceived uncertainty	Demand for additional information	Information sufficiency distinctions	Internal belief representation	Residual uncertainty	Event-level granularity	Informative signal vs insufficient noise	Observable via information requests	Sufficiency-threshold encoding	Information-acquisition update	Predictive of search or delay	Low to moderate	Correlated with uncertainty levels	Definable
Information	Perceived uncertainty	Willingness to delay to reduce uncertainty	Delay–uncertainty tradeoff distinctions	Internal belief representation	Temporal uncertainty	Event-time granularity	Uncertain-now vs clearer-later signal	Observable via timing choice	Delay-for-information encoding	Anticipatory update	Predictive of delay acceptance	Moderate	Correlated with information demand	Definable
Information	Perceived uncertainty	Conservative action selection	Downside-dominant outcome distinctions	Internal belief representation	Elevated perceived risk	Coarse outcome granularity	Downside-relevant signal vs background noise	Observable via choice	Conservative-action encoding	Experience-conditioned update	Predictive of cautious actions	Low	Correlated with safety-seeking choices	Definable
Information	Perceived uncertainty	Diversification behavior	Cross-state exposure distinctions	Internal belief representation	Distributional uncertainty	Multi-asset/state granularity	Risk-spreading signal vs idiosyncratic noise	Observable via allocation	Distributional encoding	Outcome-based updating	Predictive of variance reduction	High	Correlated across assets	Definable
Information	Perceived uncertainty	Insurance uptake thresholds	Loss-probability threshold distinctions	Internal belief representation	Tail-risk uncertainty	Binary or threshold granularity	Loss-relevant signal vs background noise	Observable via purchase choice	Threshold-based encoding	Experience-based update	Predictive of insurance adoption	Moderate	Correlated with other risk protections	Definable
Information	Perceived uncertainty	Ambiguity-sensitive switching	Ambiguity-triggered action distinctions	Internal belief representation	Ambiguity uncertainty	Option-level granularity	Ambiguity signal vs noise	Observable via choice changes	Ambiguity-responsive encoding	Ambiguity-driven update	Predictive of switching patterns	Moderate	Correlated across ambiguous contexts	Definable
Information	Perceived uncertainty	Refusal to act without information	Action-permission distinctions under ignorance	Internal belief representation	Maximal perceived uncertainty	Binary action/no-action granularity	Information-present signal vs absence	Observable via inaction	Information-gate encoding	Availability-conditioned update	Predictive of inaction under ignorance	Low	Correlated with information demand	Definable

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7. Evaluation Observables

Every item listed:

• Is directly observable
• Is evaluative, not structural
• Is non-strategic
• Is single-agent
• Requires no numerical modeling

If something:

• Quantifies desirability → Method
• Encodes uncertainty numerically → Information
• Evolves as a process → Dynamics
• Involves another agent → Interaction

…it does not belong here.

SAT – Evidence – Observables – Evaluation – Choice (Microeconomic Foundations)

Property Category	Property	Observable	Evaluated Entity / State	Evaluation Criterion	Comparator / Reference	Ordering Type	Direction of Preference	Aggregation Rule	Context / Domain of Validity	Optimality Concept	Tradeoff Structure	Tolerance / Acceptability Margin	Stability of Evaluation	Justification Type
Evaluation	Utility / value function	Chosen outcomes over rejected outcomes	Outcome	Preference	Rejected outcomes	Binary acceptable / unacceptable	Chosen is better	Implicit (single criterion)	Choice context	Local optimum	Opportunity cost	Indifference band (if any)	Fixed	Axiomatic
Evaluation	Utility / value function	Repeated selection of the same option	Option	Consistency of preference	Alternative options	Ranking	Repeatedly chosen is better	Implicit	Repeated-choice context	Satisficing or local optimum	Foregone alternatives	Small deviations tolerated	Fixed	Axiomatic
Evaluation	Utility / value function	Tradeoffs accepted between attributes (e.g., more of X for less of Y)	Outcome configuration	Attribute valuation	Alternative attribute bundles	Partial order	Direction defined by tradeoff	Weighted combination	Attribute-tradeoff context	Local optimum	Explicit attribute tradeoffs	Indifference band	Fixed	Axiomatic
Evaluation	Utility / value function	Sacrifices accepted to obtain preferred outcomes	Outcome trajectory	Net preference	Less-preferred feasible outcomes	Ranking	Preferred outcome is better	Implicit	Sacrifice-allowing context	Satisficing	Opportunity cost	Acceptable sacrifice margin	Fixed	Axiomatic
Evaluation	Utility / value function	Option abandonment in favor of alternatives	Option set	Relative preference	Abandoned option	Ranking	Alternative is better	Implicit	Menu-change context	Local optimum	Switching cost	Small loss tolerance	Fixed	Axiomatic
Evaluation	Utility / value function	Persistence in pursuing certain outcomes	Outcome trajectory	Preference persistence	Alternative outcomes	Ranking	Persisted outcome is better	Implicit	Repeated-choice context	Satisficing	Foregone alternatives	Small deviation tolerated	Fixed	Axiomatic
Evaluation	Utility / value function	Willingness to incur costs for specific outcomes	Outcome	Net preference	Lower-cost alternatives	Ranking	Preferred outcome outweighs cost	Implicit	Cost-incurring context	Local optimum	Explicit cost–benefit tradeoff	Acceptable cost margin	Fixed	Axiomatic
Evaluation	Utility / value function	Threshold behavior (won’t choose below X)	Outcome	Minimum acceptability	Threshold baseline	Binary acceptable / unacceptable	Above-threshold is better	Threshold-based	Threshold-evaluation context	Satisficing	Discrete cutoff	Indifference band at threshold	Fixed	Axiomatic
Evaluation	Utility / value function	Option dominance in repeated choices	Option	Dominance	Other options	Total or partial order	Dominant option is better	Implicit	Repeated-menu context	Local optimum	Opportunity cost	Small deviations tolerated	Fixed	Axiomatic
Evaluation	Utility / value function	Outcome substitution behavior	Outcome configuration	Relative valuation	Replaced outcome	Partial order	Substitute preferred over replaced	Implicit	Substitution context	Local optimum	Substitution tradeoff	Indifference band	Fixed	Axiomatic
Evaluation	Risk attitude	Choice of risky vs safe options	Outcome	Risk preference	Safe alternative	Binary acceptable / unacceptable or ranking	Lower risk preferred (risk-averse) or higher risk preferred (risk-seeking)	Implicit	Risky-choice context	Satisficing or local optimum	Risk–return tradeoff	Indifference band	Fixed	Axiomatic
Evaluation	Risk attitude	Insurance purchase or refusal	Outcome	Risk reduction	Uninsured baseline	Binary acceptable / unacceptable	Insured state preferred (if risk-averse)	Implicit	Loss-risk context	Satisficing	Premium vs loss tradeoff	Acceptable premium margin	Fixed	Axiomatic
Evaluation	Risk attitude	Acceptance or rejection of lotteries	Outcome	Expected risk acceptability	Certain outcome	Binary acceptable / unacceptable	Accepted lottery preferred	Implicit	Lottery-choice context	Satisficing	Risk vs certainty tradeoff	Acceptance threshold	Fixed	Axiomatic
Evaluation	Risk attitude	Diversification vs concentration choices	Outcome configuration	Risk spreading	Concentrated allocation	Partial order	Diversified preferred (if risk-averse)	Implicit	Portfolio-choice context	Local optimum	Variance–return tradeoff	Indifference band	Fixed	Axiomatic
Evaluation	Risk attitude	Avoidance of uncertain options	Option	Uncertainty aversion	Certain option	Ranking	Certain option preferred	Implicit	Ambiguous-choice context	Satisficing	Uncertainty avoidance	Zero-tolerance zone	Fixed	Axiomatic
Evaluation	Risk attitude	Preference for guaranteed outcomes	Outcome	Certainty preference	Risky alternative	Ranking or binary acceptable/unacceptable	Guaranteed outcome preferred	Implicit	Uncertain-outcome context	Satisficing	Certainty vs risk tradeoff	Indifference band	Fixed	Axiomatic
Evaluation	Risk attitude	Switching behavior when uncertainty increases	Choice pattern	Risk sensitivity	Lower-uncertainty choice	Partial order	Lower uncertainty preferred	Implicit	Rising-uncertainty context	Local optimum	Risk escalation tradeoff	Switching threshold	Fixed	Axiomatic
Evaluation	Risk attitude	Demand for certainty premiums	Outcome	Certainty valuation	Risky baseline	Ranking	Higher certainty preferred	Implicit	Compensation-for-risk context	Satisficing	Premium vs risk tradeoff	Acceptable premium margin	Fixed	Axiomatic
Evaluation	Risk attitude	Refusal to engage under uncertainty	Action/outcome	Uncertainty aversion	Participation baseline	Binary acceptable/unacceptable	Non-engagement preferred	Implicit	High-uncertainty context	Satisficing	Participation vs uncertainty	Zero-tolerance zone	Fixed	Axiomatic
Evaluation	Risk attitude	Consistent gambling or avoidance behavior	Choice trajectory	Risk disposition	Alternative risk posture	Ranking	Gambling or avoidance preferred	Implicit	Repeated-risk context	Local optimum	Risk–return tradeoff	Indifference band	Fixed	Axiomatic
Evaluation	Time preference	Choice of sooner vs later rewards	Reward outcome	Temporal preference	Delayed alternative	Ranking or binary acceptable/unacceptable	Sooner or later preferred	Implicit	Intertemporal choice context	Satisficing or local optimum	Time–reward tradeoff	Indifference band	Fixed	Axiomatic
Evaluation	Time preference	Saving vs immediate consumption	Consumption allocation	Intertemporal valuation	Immediate-consumption baseline	Ranking	Future consumption preferred (if patient)	Implicit	Consumption–saving context	Local optimum	Present vs future tradeoff	Acceptable delay margin	Fixed	Axiomatic
Evaluation	Time preference	Delay acceptance or rejection	Delayed outcome	Delay tolerance	Immediate alternative	Binary acceptable/unacceptable	Acceptable delay preferred	Threshold-based	Delay-evaluation context	Satisficing	Delay–benefit cutoff	Delay threshold	Fixed	Axiomatic
Evaluation	Time preference	Preference reversals over time	Outcome ordering	Temporal consistency	Prior ordering	Partial or inconsistent order	Later preference overrides earlier	Implicit	Time-varying context	Local optimum (contextual)	Inconsistent tradeoff	Indifference overlap	Variable	Behavioral
Evaluation	Time preference	Procrastination behavior	Action timing	Temporal valuation	Immediate-action baseline	Ranking	Delay preferred over immediate	Implicit	Task-timing context	Satisficing	Effort–delay tradeoff	Delay tolerance zone	Fixed	Axiomatic
Evaluation	Time preference	Front-loaded vs back-loaded consumption	Consumption timing profile	Temporal valuation	Alternative timing profile	Ranking	Front-loaded or back-loaded preferred	Implicit	Intertemporal consumption context	Local optimum	Timing–consumption tradeoff	Indifference band	Fixed	Axiomatic
Evaluation	Time preference	Early vs late effort exertion	Effort timing	Temporal cost–benefit valuation	Alternative effort timing	Ranking	Earlier or later effort preferred	Implicit	Task-execution context	Satisficing	Effort–delay tradeoff	Acceptable delay margin	Fixed	Axiomatic
Evaluation	Time preference	Waiting tolerance	Delayed outcome	Delay acceptability	Immediate outcome	Threshold / binary acceptable	Delay tolerated up to limit	Threshold-based	Waiting-decision context	Satisficing	Delay–benefit tradeoff	Waiting tolerance band	Fixed	Axiomatic
Evaluation	Time preference	Abandonment due to delay	Outcome pursuit	Delay aversion	Continued waiting baseline	Binary acceptable/unacceptable	Abandonment preferred beyond delay	Implicit	Delay-cost context	Satisficing	Delay vs payoff tradeoff	Zero-tolerance zone	Fixed	Axiomatic
Evaluation	Time preference	Timing-based switching behavior	Choice pattern over time	Temporal preference sensitivity	Prior timing choice	Partial order	New timing preferred	Implicit	Changing-delay context	Local optimum	Timing re-evaluation tradeoff	Switching threshold	Fixed	Axiomatic
Evaluation	Subjective “better vs. worse” criteria	Lexicographic choices (one attribute dominates all others)	Outcome configuration	Attribute priority	Any alternative differing on dominant attribute	Lexicographic order	Dominant attribute higher is better	Lexicographic (no aggregation)	Attribute-priority context	Lexicographic optimum	No tradeoffs allowed	Zero tolerance	Fixed	Axiomatic
Evaluation	Subjective “better vs. worse” criteria	Rule-based exclusions (“never choose X”)	Option	Prohibition rule	All other options	Binary acceptable / unacceptable	Non-excluded options preferred	Rule-based (exclusion)	Rule-governed context	Satisficing (by exclusion)	No compensating tradeoffs	Zero tolerance	Fixed	Deontic / axiomatic
Evaluation	Subjective “better vs. worse” criteria	Satisficing behavior	Outcome	Acceptability threshold	Minimum acceptable standard	Binary or partial order	Meets threshold is better	Threshold rule	Bounded-rationality context	Satisficing	Tradeoffs ignored beyond threshold	Acceptability band	Fixed	Behavioral
Evaluation	Subjective “better vs. worse” criteria	Threshold rules	Outcome	Minimum/maximum criterion	Threshold baseline	Binary acceptable / unacceptable	Above/below threshold preferred	Threshold-based	Threshold-evaluation context	Satisficing	Discrete cutoff	Threshold band	Fixed	Axiomatic
Evaluation	Subjective “better vs. worse” criteria	Moral or categorical refusals	Action or outcome	Moral/categorical rule	All feasible alternatives	Binary prohibition	Refused options always worse	Rule-based (categorical)	Moral/categorical context	No-optimum (exclusion)	No tradeoffs permitted	Zero tolerance	Fixed	Ethical / deontic
Evaluation	Subjective “better vs. worse” criteria	Priority-based decision rules	Outcome configuration	Attribute priority	Alternatives differing on higher-priority attribute	Lexicographic or priority order	Higher-priority satisfaction is better	Priority rule (non-compensatory)	Priority-rule context	Lexicographic optimum	No compensating tradeoffs	Zero tolerance	Fixed	Axiomatic
Evaluation	Subjective “better vs. worse” criteria	Attribute veto behavior	Outcome configuration	Veto condition	Any option violating veto attribute	Binary acceptable / unacceptable	Non-vetoed options preferred	Veto rule	Veto-governed context	Satisficing by exclusion	Absolute veto (no tradeoff)	Zero tolerance	Fixed	Deontic / axiomatic
Evaluation	Subjective “better vs. worse” criteria	All-or-nothing choices	Outcome	Completeness requirement	Partial or compromised outcomes	Binary order	Fully meeting criterion is better	Binary rule	All-or-nothing context	Satisficing	No partial compensation	Zero tolerance	Fixed	Axiomatic
Evaluation	Subjective “better vs. worse” criteria	Hard preferences insensitive to tradeoffs	Option or outcome	Non-compensatory preference	Any alternative	Total or partial order	Preferred option always better	Non-compensatory	Tradeoff-insensitive context	Lexicographic / fixed optimum	Tradeoffs ignored	Zero tolerance	Fixed	Axiomatic
Evaluation	Subjective “better vs. worse” criteria	Context-independent evaluative rules	Outcome	Context invariance	Same outcome across contexts	Stable ranking	Same ordering everywhere	Implicit	Cross-context validity	Context-invariant optimum	Fixed tradeoff structure	Indifference band (if any)	Fixed	Axiomatic

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