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

Author

Listed:
  • Luisa Bisaglia

    (Department of Statistics, University of Padova)

  • Margherita Gerolimetto

    (Department of Economics, Ca' Foscari University of Venice)

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.

Suggested Citation

  • Luisa Bisaglia & Margherita Gerolimetto, "undated". "Estimation and forecasting in INAR(p) models using sieve bootstrap," Working Papers 2018:06, Department of Economics, University of Venice "Ca' Foscari".
    • Handle: RePEc:ven:wpaper:2018:06
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    More about this item

    Keywords

    INAR(p) models; estimation; forecast; bootstrap;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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