Modeling Zero Inflation in Count Data Time Series with Bounded Support

Tobias A. Möller, Christian H. Weiß, Hee-Young Kim () and Andrei Sirchenko
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Tobias A. Möller: Helmut Schmidt University
Christian H. Weiß: Helmut Schmidt University
Hee-Young Kim: Korea University

Methodology and Computing in Applied Probability, 2018, vol. 20, issue 2, 589-609

Abstract: 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; 62M10; 91B70; 60G10; 60J10 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s11009-017-9577-0

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