Nonparametric Testability of Slutsky Symmetry
Florian Gunsilius, Lonjezo Sithole

TL;DR
This paper develops a nonparametric testing method for Slutsky symmetry, a key rationality condition in consumer demand theory, accounting for heterogeneity and endogeneity, with broad implications for econometric analysis.
Contribution
It derives the first nonparametric conditional quantile restrictions that test Slutsky symmetry in complex settings with heterogeneity and endogeneity, extending identification theory.
Findings
Established nonparametric testable implications of Slutsky symmetry.
Provided a multivariate generalization of identification in nonseparable models.
Implications for nonparametric welfare analysis with multiple goods.
Abstract
Economic theory implies strong limitations on what types of consumption behavior are considered rational. Rationality implies that the Slutsky matrix, which captures the substitution effects of compensated price changes on demand for different goods, is symmetric and negative semi-definite. While empirically informed versions of negative semi-definiteness have been shown to be nonparametrically testable, the analogous question for Slutsky symmetry has remained open. Recently, it has even been shown that the symmetry condition is not testable via the average Slutsky matrix, prompting conjectures about its non-testability. We settle this question by deriving nonparametric conditional quantile restrictions on observable data that constitute a testable implication of Slutsky symmetry in an empirical setting with individual heterogeneity and endogeneity. The theoretical contribution is a…
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Taxonomy
TopicsEconomics of Agriculture and Food Markets · Consumer Market Behavior and Pricing · Advanced Causal Inference Techniques
