Subjective Time Deformation in Intertemporal Choice: A Functional Data Analysis Approach
This study addresses a key limitation in traditional intertemporal choice research, which relies on scalar discount rates or prespecified functional forms and thus fails to capture the full trajectory of individuals’ subjective time perception. For the first time, functional data analysis is introduced to this domain: based on discrete intertemporal equivalence judgments, the authors employ monotonic smoothing to reconstruct each individual’s implicit subjective time trajectory. Combining functional principal component analysis with clustering, they systematically uncover substantial heterogeneity in these trajectories. The first two principal components account for 97.44% of total variation, and clustering yields three robust and stable temporal distortion patterns. Although conventional parametric models achieve good fit, they cannot replicate this underlying structure. Notably, implicit time trajectories only partially align with explicit time perception measures, underscoring the unique capacity of functional approaches to reveal complex temporal preferences.