Un sistema ARIMA con agregación temporal para la previsión y el seguimiento del déficit del Estado
AbstractOur 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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Bibliographic InfoArticle provided by IEF in its journal Hacienda Pública Española/Revista de Economía Pública.
Volume (Year): 190 (2009)
Issue (Month): 3 (June)
Fiscal forecasting; time series analysis; monitoring; forecasting; public deficit;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- 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
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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