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Generalized Integer-Valued Autoregression

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Author Info

  • Brännäs, Kurt

    ()
    (Department of Economics, Umeå University)

  • Hellström, Jörgen

    ()
    (Department of Economics, Umeå University)

Abstract

The integer-valued AR(1) model is generalized to encompass some of the more likely features of economic time series of count data. The generalizations come at the price of loosing exact distributional properties. For most specifications the first and second order both conditional and unconditional moments can be obtained. Hence estimation, testing and forecasting are feasible and can be based on least squares or GMM techniques. An illustration based on the number of plants within an industrial sector is considered.

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Bibliographic Info

Paper provided by Umeå University, Department of Economics in its series Umeå Economic Studies with number 501.

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Length: 21 pages
Date of creation: 14 Apr 1999
Date of revision:
Publication status: Published in Econometric Reviews, 2001, pages 425-443.
Handle: RePEc:hhs:umnees:0501

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Postal: Department of Economics, Umeå University, S-901 87 Umeå, Sweden
Phone: 090 - 786 61 42
Fax: 090 - 77 23 02
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Web page: http://www.econ.umu.se/
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Keywords: Characterization; Dependence; Time series model; Estimation; Forecasting; Entry and exit;

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Cited by:
  1. Francesco Bravo, 2011. "Comment on: Subsampling weakly dependent time series and application to extremes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 20(3), pages 483-486, November.
  2. Daunfeldt, Sven-Olov & Orth, Matilda & Rudholm, Niklas, 2008. "Does the Quality of Store Brands Affect the Number of National Brand Suppliers?," HUI Working Papers 18, HUI Research.
  3. 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.
  4. Hellström, Jörgen & Simonsen, Ola, 2006. "Does the Open Limit Order Book Reveal Information About Short-run Stock Price Movements?," UmeÃ¥ Economic Studies 687, Umeå University, Department of Economics.
  5. Jung, Robert C. & Tremayne, A.R., 2006. "Coherent forecasting in integer time series models," International Journal of Forecasting, Elsevier, vol. 22(2), pages 223-238.
  6. Yousung Park & Hee-Young Kim, 2012. "Diagnostic checks for integer-valued autoregressive models using expected residuals," Statistical Papers, Springer, vol. 53(4), pages 951-970, November.
  7. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330.
  8. Andersson, Jonas & Karlis, Dimitris, 2008. "Treating missing values in INAR(1) models," Discussion Papers 2008/14, Department of Business and Management Science, Norwegian School of Economics.

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