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Monitoring and forecasting annual public deficit every month: the case of France

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  • Andrea Silvestrini
  • Matteo Salto
  • Laurent Moulin
  • David Veredas

    ()

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 34 (2008)
Issue (Month): 3 (June)
Pages: 493-524

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Handle: RePEc:spr:empeco:v:34:y:2008:i:3:p:493-524

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Related research

Keywords: French state deficit; Temporal aggregation; Intra-annual; Forecasting; C22; C53; E62; H60;

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References

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  1. Andrea, SILVESTRINI, 2005. "Temporal aggregaton of univariate linear time series models," Discussion Papers (ECON - Département des Sciences Economiques) 2005044, Université catholique de Louvain, Département des Sciences Economiques.
  2. William W. S. Wei, 1978. "Some Consequences of Temporal Aggregation in Seasonal Time Series Models," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 433-448 National Bureau of Economic Research, Inc.
  3. Bretschneider, Stuart I. & Gorr, Wilpen L. & Grizzle, Gloria & Klay, Earle, 1989. "Political and organizational influences on the accuracy of forecasting state government revenues," International Journal of Forecasting, Elsevier, vol. 5(3), pages 307-319.
  4. Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
  5. Drost, F.C. & Nijman, T.E., 1992. "Temporal Aggregation of Garch Processes," Papers 9240, Tilburg - Center for Economic Research.
  6. Santos Silva, J. M. C. & Cardoso, F. N., 2001. "The Chow-Lin method using dynamic models," Economic Modelling, Elsevier, vol. 18(2), pages 269-280, April.
  7. Palm, Franz C & Nijman, Theo E, 1984. "Missing Observations in the Dynamic Regression Model," Econometrica, Econometric Society, vol. 52(6), pages 1415-35, November.
  8. Nijman, Theo E & Palm, Franz C, 1990. "Predictive Accuracy Gain from Disaggregate Sampling in ARIMA Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(4), pages 405-15, October.
  9. Gonzalo Camba-Mendez & Ana Lamo, 2004. "Short-term monitoring of fiscal policy discipline," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 247-265.
  10. Yue Fang & Sergio G. Koreisha, 2004. "Updating ARMA predictions for temporal aggregates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(4), pages 275-296.
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Cited by:
  1. Helmut Luetkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo Group Munich.
  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. Teresa Leal & Diego Pedregal & Javier Pérez, 2011. "Short-term monitoring of the Spanish government balance," SERIEs, Spanish Economic Association, vol. 2(1), pages 97-119, March.
  4. Laura Carabotta, 2014. "Which Agency and Which Period is The Best? Analyzing National and International Fiscal Forecasts in Italy," International Journal of Economic Sciences, University of Economics, Prague, vol. 2014(1), pages 27-46.
  5. 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.
  6. Leal, Teresa & Pérez, Javier J. & Tujula, Mika & Vidal, Jean-Pierre, 2007. "Fiscal forecasting: lessons from the literature and challenges," Working Paper Series 0843, European Central Bank.
  7. Ramirez, Octavio A., 2012. "Conclusive Evidence on the Benefits of Temporal Disaggregation to Improve the Precision of Time Series Model Forecasts," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123470, Agricultural and Applied Economics Association.
  8. Ramirez, Octavio A., 2011. "Conclusive Evidence on the Benefits of Temporal Disaggregation to Improve the Precision of Time Series Model Forecasts," Faculty Series 113520, University of Georgia, Department of Agricultural and Applied Economics.

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