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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.

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Article provided by IEF in its journal Hacienda Pública Española/Revista de Economía Pública.

Volume (Year): 190 (2009)
Issue (Month): 3 (June)
Pages: 27-58

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Handle: RePEc:hpe:journl:y:2009:v:190:i:3:p:27-58
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  1. Pedregal, Diego J. & Pérez, Javier J., 2008. "Should quarterly government finance statistics be used for fiscal surveillane in Europe?," Working Paper Series 0937, European Central Bank.
  2. 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.
  3. 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.
  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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