Using intra annual information to forecast the annual state deficits: the case of France

Laurent Moulin, Matteo Salto, Andrea Silvestrini and David Veredas

No 2004048, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: We develop a methodology for using intra-annual data to forecast annual budget deficits. Our approach aims at improving the accuracy of the deficit forecasts, a relevant issue to policy makers in the Eurozone and at proposing a replicable methodology using at best public quantitative information on budgetary data. Using French data on government (State) revenues and expenditures, we estimate intra-annual monthly ARIMA models for all the items of the central government revenues and expenditures. Next, applying temporal aggregation techniques, we infer parameters of the annual models from the estimated parameters of the intra-annual models. These parameters incorporate all the intra-annual information. Finally, we do one period ahead predictions. We are able to update the annual deficit forecast as soon as new monthly data are available. This allows us to detect possible slippages in central government finances.

Keywords: French State deficit; temporal aggregation; intra-annual; forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 E62 H60 (search for similar items in EconPapers)
Date: 2004-07
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Working Paper: Using intra annual information to forecast the annual state deficit. The case of France (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2004048

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