Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/273849 
Year of Publication: 
2023
Series/Report no.: 
Tinbergen Institute Discussion Paper No. TI 2023-038/III
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
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.
Subjects: 
Bayesian Inference
Mixture Models
Mode Inference
Multimodality
Shifted-Poisson.
JEL: 
C11
C25
C81
C82
E00
D00
Document Type: 
Working Paper

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