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Un sistema ARIMA con agregación temporal para la previsión y el seguimiento del déficit del Estado


  • Teresa Leal Linares

    () (Universidad de Huelva)

  • Javier J. Pérez

    () (Banco de España)


Our aim is to develop a temporal aggregation ARIMA model to monitor and forecast the annual Spanish central government deficit in order to detect in advance a possible deterioration of the annual public sector balance, using monthly data. We compare the predictive performance of the proposed model with competing forecasting methods, such as annual forecasts directly derived from monthly ARIMA models, and official forecasts published by the government. The results confirm the large improvement in forecasting performance of the aggregated ARIMA system when compared to other alternatives.

Suggested Citation

  • Teresa Leal Linares & Javier J. Pérez, 2009. "Un sistema ARIMA con agregación temporal para la previsión y el seguimiento del déficit del Estado," Hacienda Pública Española, IEF, vol. 190(3), pages 27-58, June.
  • Handle: RePEc:hpe:journl:y:2009:v:190:i:3:p:27-58

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    References listed on IDEAS

    1. Andrea Silvestrini & Matteo Salto & Laurent Moulin & David Veredas, 2008. "Monitoring and forecasting annual public deficit every month: the case of France," Empirical Economics, Springer, vol. 34(3), pages 493-524, June.
    2. Onorante, Luca & Pedregal, Diego J. & Pérez, Javier J. & Signorini, Sara, 2010. "The usefulness of infra-annual government cash budgetary data for fiscal forecasting in the euro area," Journal of Policy Modeling, Elsevier, vol. 32(1), pages 98-119, January.
    3. Pedregal, Diego J. & Pérez, Javier J., 2010. "Should quarterly government finance statistics be used for fiscal surveillance in Europe?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 794-807, October.
    4. Perez, Javier J., 2007. "Leading indicators for euro area government deficits," International Journal of Forecasting, Elsevier, vol. 23(2), pages 259-275.
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    More about this item


    Fiscal forecasting; time series analysis; monitoring; forecasting; public deficit;

    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
    • H68 - Public Economics - - National Budget, Deficit, and Debt - - - Forecasts of Budgets, Deficits, and Debt


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