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Bayesian Mode Inference for Discrete Distributions in Economics and Finance

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  • Jamie L. Cross
  • Lennart Hoogerheide
  • Paul Labonne
  • Herman K. van Dijk

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.

Suggested Citation

  • Jamie L. Cross & Lennart Hoogerheide & Paul Labonne & Herman K. van Dijk, 2023. "Bayesian Mode Inference for Discrete Distributions in Economics and Finance," Working Papers No 11/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    • Handle: RePEc:bny:wpaper:0122
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    File URL: https://hdl.handle.net/11250/3095578
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    References listed on IDEAS

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