Bayesian Mode Inference for Discrete Distributions in Economics and Finance

Jamie Cross, Lennart Hoogerheide (), Paul Labonne () and Herman van Dijk

No No 11/2023, Working Papers from Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School

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.

Pages: 11 pages
Date: 2023-06
New Economics Papers: this item is included in nep-cba, nep-fdg and nep-mon
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https://hdl.handle.net/11250/3095578

Related works:
Journal Article: Bayesian mode inference for discrete distributions in economics and finance (2024)
Working Paper: Bayesian Mode Inference for Discrete Distributions in Economics and Finance (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:bny:wpaper:0123

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