Bayesian Mode Inference for Discrete Distributions in Economics and Finance - Jamie Cross; Lennart Hoogerheide; Paul Labonne; Herman K. van Dijk (Tinbergen Institute, 2023)
Detecting heterogeneity within a population is crucial in many economic and financial applications. Econometrically, this requires a credible determination of multimodality in a given data distribution. We propose a straightforward yet effective technique for mode inference in discrete data distributions which involves fitting a mixture of novel shifted-Poisson distributions. The credibility and utility of our proposed approach is demonstrated through empirical investigations on datasets pertaining to loan default risk and inflation expectations.
Keywords: C11; C25; C81; C82; E00; D00; 330; Bayesian Inference; Mixture Models; Mode Inference; Multimodality; Shifted-Poisson.