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Vector-Autoregression Approach to Forecast Italian Imports

Author

Listed:
  • Carmine Pappalardo

    (ISAE - Institute for Studies and Economic Analyses)

  • Gianfranco Piras

    (University of Pescara, Faculty of Economics)

Abstract

Imports represent a relevant component of total economic resources. For the Italian case, they mainly consist of raw materials and intermediate goods. In this paper, we evaluate several econometric models performing shorthorizon forecasts of Italian imports of goods. Year-to-year growth rate of the monthly seasonally unadjusted series is the variable to predict. VAR forecasting ability has been compared to that of a linear univariate benchmark (ARIMA) model. Main forecast diagnostics have been presented. Finally, we perform two types of forecast encompassing tests (Diebold-Mariano, 1995; Fair-Shiller, 1990) for which we present main results.

Suggested Citation

  • Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    • Handle: RePEc:isa:wpaper:42
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    References listed on IDEAS

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    Cited by:

    1. Grimme, Christian & Lehmann, Robert & Noeller, Marvin, 2021. "Forecasting imports with information from abroad," Economic Modelling, Elsevier, vol. 98(C), pages 109-117.

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    More about this item

    Keywords

    Forecasting; VAR model; Import; Forecast evaluation.;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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