Estimation and forecasting in INAR(p) models using sieve bootstrap

Luisa Bisaglia () and Margherita Gerolimetto ()
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Luisa Bisaglia: Department of Statistics, University of Padova
Margherita Gerolimetto: Department of Economics, Ca' Foscari University of Venice

No 2018:06, Working Papers from Department of Economics, University of Venice "Ca' Foscari"

Abstract: In this paper we analyse some bootstrap techniques to make inference in INAR(p) models. First of all, via Monte Carlo experiments we compare the performances of these methods when estimating the thinning parameters in INAR(p) models. We state the superiority of sieve bootstrap approaches on block bootstrap in terms of low bias and Mean Square Error (MSE). Then we apply the sieve bootstrap methods to obtain coherent predictions and confidence intervals in order to avoid difficulty in deriving the distributional properties.

Keywords: INAR(p) models; estimation; forecast; bootstrap (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Pages: 29 pages
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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Persistent link: https://EconPapers.repec.org/RePEc:ven:wpaper:2018:06

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