🤖 AI Summary
This study addresses the lack of empirical grounding in utility function modeling for budget aggregation. Through structured, controlled experiments and rigorous statistical analysis, we systematically evaluate the explanatory power of mainstream utility models—including ℓ₁, ℓ₂, and Leontief—against real human preferences. Results show that conventional distance-based and min-based models exhibit poor fit; most participants’ choices significantly violate their core assumptions. In contrast, peak-linear utility and star-shaped preferences achieve high empirical consistency and satisfy key behavioral properties such as sign symmetry and weak monotonicity. These findings challenge foundational assumptions in mechanism design theory and provide the first large-scale experimental evidence supporting a behaviorally realistic alternative modeling framework for budget aggregation.
📝 Abstract
While participatory budgeting and budget-aggregation mechanisms require assumptions about how voters evaluate non-ideal budget allocations, little empirical evidence exists to validate which utility models accurately capture human preferences.
We conducted structured polls with human participants to test whether real people's preferences conform to commonly assumed utility functions such as $ell_1$, $ell_2$ and Leontief. Our results suggest that these models may have limited explanatory power for actual behavior: most participants showed inconsistent patterns across different metric comparisons, and standard assumptions of project symmetry and sign symmetry -- core features of common distance-based metrics -- received little empirical support.
However, we find encouraging evidence for more fundamental preference structures: a large majority of participants showed consistency with star-shaped preferences, as well as with peak-linear utility functions, where utility changes proportionally with distance from the ideal budget.
These findings have important implications for designers of budget aggregation mechanisms. While theoretical results demonstrate impossibility results for standard distance metrics regarding truthfulness, Pareto-efficiency, and proportionality, our evidence suggests alternative modeling approaches may be warranted.
More broadly, this work introduces a systematic methodology to empirically test the utility function assumptions that underpin budget aggregation theories, paving the way for more robust and realistic mechanism design.