Theoretical Foundations#

This chapter delineates the formal notation, foundational assumptions, and axiomatic hierarchy that constitute the theoretical core of revealed preference analysis.

Formal Notation#

The analysis of choice behavior in PrefGraph is based on the following mathematical conventions:

\(p^t \in \mathbb{R}^n_+\)

Price vector associated with observation \(t\).

\(x^t \in \mathbb{R}^n_+\)

Commodity bundle (quantity vector) selected at observation \(t\).

\(e_t = p^t \cdot x^t\)

Total expenditure at observation \(t\).

\(E_{ij} = p^i \cdot x^j\)

The hypothetical cost of bundle \(j\) evaluated at the price vector of observation \(i\).

\(T\)

Total number of longitudinal observations for a given agent.

\(n\)

Dimensionality of the commodity space (number of distinct goods).

Maintained Assumptions#

The validity of revealed preference results is contingent upon several maintained assumptions regarding the underlying data-generating process. Violations of these assumptions may lead to spurious detections of behavioral inconsistency.

Assumption

Implications of Violation

A1

Preference Stability - The agent possesses a time-invariant utility function \(U(x)\) across all observations.

Evolutionary changes in preferences (e.g., taste formation) may be incorrectly identified as axiomatic violations.

A2

Utility Maximization - Observed choices represent the solution to \(\arg\max_x U(x)\) subject to the budget constraint.

Decision heuristics, cognitive load, or satisficing behavior generate violations that reflect bounded rationality.

A3

Local Non-Satiation - The agent strictly prefers more of at least one good; the entire budget is exhausted.

While free disposal is mathematically accommodated, systematic under-spending or unobserved saving violates the budget model.

A4

Unitary Decision-Maker - Observed choices reflect the preferences of a single optimizing agent.

Aggregated household data or multi-user accounts may exhibit violations arising from collective choice dynamics.

A5

Information Completeness - The analyst observes the exhaustive set of commodities and prices relevant to the agent’s decision.

Partial observation (e.g., omitting essential categories) may result in an incomplete budget set, leading to false-positive violations.

Axiomatic Hierarchy#

The fundamental axioms of revealed preference exhibit a nested hierarchical structure, providing varying levels of stringency for behavioral analysis.

Logical Relationship Between Axioms

SARP \(\Rightarrow\) GARP \(\Rightarrow\) WARP

  • WARP (Weak Axiom): Precludes direct contradictions in pairwise choices (cycles of length 2).

  • GARP (Generalized Axiom): Precludes transitive contradictions across cycles of any length, provided at least one preference is strict.

  • SARP (Strong Axiom): Precludes all preference cycles, including those involving indifference; it is the most restrictive condition.

Empirical applications typically focus on GARP, as it provides the necessary and sufficient conditions for rationalizability by a continuous, monotonic, and concave utility function (Afriat, 1967).

Note

Axiomatic Selection Criteria:

  • WARP: Employed as a computationally efficient preliminary filter for direct inconsistencies.

  • GARP: The standard benchmark for consumer rationality and utility maximization.

  • SARP: Required for applications necessitating unique demand systems or differentiable utility specifications.