Empirical validation of utility theory: Constructing utility functions from consumer survey data to validate the stability of risk preference parameters.

Introduction

Utility theory, a cornerstone of economic decision-making, posits that individuals assign cardinal values to outcomes to reflect their preferences. This framework, rooted in von Neumann-Morgenstern utility functions, assumes rationality and consistency in decision-making. However, empirical validation remains critical to confirm the theoretical underpinnings of utility theory, particularly in contexts where behavioral deviations are observed. While theoretical models provide a foundational structure, real-world data often reveal complexities such as risk aversion, loss aversion, and the impact of psychological factors on utility. This study aims to empirically validate utility theory by constructing utility functions from consumer survey data, thereby assessing the stability of risk preference parameters. By analyzing survey responses across diverse scenarios, the study seeks to bridge the gap between abstract theoretical constructs and observable human behavior, offering insights into the robustness of risk preference parameters in economic decision-making.

Methodology

The empirical validation process involves three primary stages: data collection, model construction, and parameter estimation. First, consumer survey data is collected through structured questionnaires, capturing preferences for various outcomes (e.g., financial gains, risks, or losses). Data are anonymized to ensure privacy, and variables such as risk tolerance, expected utility, and decision-making frameworks are systematically recorded. Next, data processing involves cleaning and normalization to eliminate inconsistencies, such as missing values or outliers. This step ensures the reliability of subsequent analyses.

Model construction relies on the framework of expected utility theory, which assumes that