Animal Welfare and Policy Risk Index (AWPRI): Constructing and Validating a Cross-National Governance Risk Measure, 25 Countries, 2004-2022

Jason Hung

Papers from arXiv.org

Abstract: This paper introduces the Animal Welfare and Policy Risk Index (AWPRI), a composite risk index covering 25 countries over the period 2004-2022 (N=475 country-year observations). The AWPRI is constructed from 15 variables organised across three equal-weighted conceptual layers: Current Welfare State (L1), Policy Trajectory (L2), and AI Amplification Risk (L3). Variables are normalised to [0, 1] using min-max scaling, with higher values denoting greater policy risk. The index is validated through k-means cluster analysis (k=4; silhouette coefficient=0.447), principal component analysis (PCA) of the 15-variable cross-section, and sensitivity analysis under +/- 10 percentage-point layer weight perturbation (mean Spearman \r{ho}=0.993, minimum 0.979; mean Adjusted Rand Index (ARI)=0.684, range 0.477-1.000). Our Hausman specification test favours random-effects (RE) panel estimation (H=2.55, p=0.467). We use a difference-in-differences (DiD) design to exploit the 2019 AI governance risk classification divergence and find that countries identified as high-AI-governance-risk carry AWPRI scores 0.080 points higher than their low-risk counterparts, after controlling for country and year fixed effects (\b{eta}=0.080, SE=0.005, p

Date: 2026-03, Revised 2026-04
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