Modeling Zero Inflation in Count Data Time Series with Bounded Support

  • Tobias A. Möller
  • Christian H. Weiß
  • Hee-Young Kim
  • Andrei Sirchenko
Article
  • 80 Downloads

Abstract

Real count data time series often show an excessive number of zeros, which can form quite different patterns. We develop four extensions of the binomial autoregressive model for autocorrelated counts with a bounded support, which can accommodate a broad variety of zero patterns. The stochastic properties of these models are derived, and ways of parameter estimation and model identification are discussed. The usefulness of the models is illustrated, among others, by an application to the monetary policy decisions of the National Bank of Poland.

Keywords

Binomial distribution Count data time series Hidden Markov model Markov model Zero inflation 

Mathematics Subject Classifications (2010)

62M10 91B70 60G10 60J10 

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Notes

Acknowledgements

The authors thank the referee for carefully reading the article and for the comments, which greatly improved the article. H.-Y. Kim’s study is supported by the project “Small & Medium Business Administration” under Project S2312692 “Technological Innovation Development Business” for the innovative company in the year 2015. Main parts of this research were completed while H.-Y. Kim stayed as a guest professor at the Helmut Schmidt University in Hamburg.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsHelmut Schmidt UniversityHamburgGermany
  2. 2.Division of Economics and Statistics, National StatisticsKorea UniversitySejongSouth Korea
  3. 3.Department of EconomicsHigher School of EconomicsMoscowRussia

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