Arbeitspapier

Bayesian Mode Inference for Discrete Distributions in Economics and Finance

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.

Language
Englisch

Bibliographic citation
Series: Tinbergen Institute Discussion Paper ; No. TI 2023-038/III

Classification
Wirtschaft
Bayesian Analysis: General
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
Macroeconomics and Monetary Economics: General
Microeconomics: General
Subject
Bayesian Inference
Mixture Models
Mode Inference
Multimodality
Shifted-Poisson.

Event
Geistige Schöpfung
(who)
Cross, Jamie
Hoogerheide, Lennart
Labonne, Paul
van Dijk, Herman K.
Event
Veröffentlichung
(who)
Tinbergen Institute
(where)
Amsterdam and Rotterdam
(when)
2023

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Cross, Jamie
  • Hoogerheide, Lennart
  • Labonne, Paul
  • van Dijk, Herman K.
  • Tinbergen Institute

Time of origin

  • 2023

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