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Estimation in integer‐valued moving average models

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  • Kurt Brännäs
  • Andreia Hall

Abstract

The paper presents new characterizations of the integer‐valued moving average model. For four model variants, we give moments and probability generating functions. Yule–Walker and conditional least‐squares estimators are obtained and studied by Monte Carlo simulation. A new generalized method of moment estimator based on probability generating functions is presented and shown to be consistent and asymptotically normal. The small sample performance is in some instances better than those of alternative estimators. Copyright © 2001 John Wiley & Sons, Ltd.

Suggested Citation

  • Kurt Brännäs & Andreia Hall, 2001. "Estimation in integer‐valued moving average models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 17(3), pages 277-291, July.
    • Handle: RePEc:wly:apsmbi:v:17:y:2001:i:3:p:277-291
    DOI: 10.1002/asmb.445
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    Cited by:

    1. Chen, Zezhun & Dassios, Angelos, 2022. "Cluster point processes and Poisson thinning INARMA," LSE Research Online Documents on Economics 113652, London School of Economics and Political Science, LSE Library.
    2. Brännäs, Kurt, 2002. "Conditional Heteroskedasticity in some Common Count Data Models for Financial Time Series Data," Umeå Economic Studies 592, Umeå University, Department of Economics.
    3. Christian H. Weiß & Martin H.-J. M. Feld & Naushad Mamode Khan & Yuvraj Sunecher, 2019. "INARMA Modeling of Count Time Series," Stats, MDPI, vol. 2(2), pages 1-37, June.
    4. Kimberly F. Sellers & Ali Arab & Sean Melville & Fanyu Cui, 2021. "A flexible univariate moving average time-series model for dispersed count data," Journal of Statistical Distributions and Applications, Springer, vol. 8(1), pages 1-12, December.
    5. Schatz, Michael & Wheatley, Spencer & Sornette, Didier, 2022. "The ARMA Point Process and its Estimation," Econometrics and Statistics, Elsevier, vol. 24(C), pages 164-182.
    6. Brannas, Kurt & Hellstrom, Jorgen & Nordstrom, Jonas, 2002. "A new approach to modelling and forecasting monthly guest nights in hotels," International Journal of Forecasting, Elsevier, vol. 18(1), pages 19-30.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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