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Exploring the dynamics of business survey data using Markov models

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Publication:2010373
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DOI10.1007/s10287-019-00354-4OpenAlexW2963408285MaRDI QIDQ2010373

W. Hölzl, Yuri M. Kaniovski, Serguei Kaniovski

Publication date: 27 November 2019

Published in: Computational Management Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10287-019-00354-4


zbMATH Keywords

business cyclemultinomial distributioncoupled Markov chainbusiness tendency surveys


Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Nonlinear programming (90C30) Operations research and management science (90Bxx)


Related Items

Numerical estimates of risk factors contingent on credit ratings



Cites Work

  • A coupled Markov chain approach to credit risk modeling
  • Latent variable models for the analysis of socio-economic data
  • Modeling dependent credit rating transitions: a comparison of coupling schemes and empirical evidence
  • Business cycle durations
  • Finite mixture and Markov switching models.
  • Latent Variable Modelling: A Survey*
  • A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
  • Identification of hidden Markov chains governing dependent credit-rating migrations
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