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A toolkit to strengthen government budget surveillance

Listed author(s):
  • Diego J. Pedregal

    ()

    (U. Castilla la Mancha)

  • Javier J. Pérez

    ()

    (Banco de España)

  • A. Jesús Sánchez-Fuentes

    ()

    (U. Complutense de Madrid)

In this paper we develop a comprehensive short-term fiscal forecasting system of use for the real-time monitoring of the Spanish government’s borrowing requirement. Spain has been at the centre of the recent European sovereign debt crisis, not least because of sizeable failures in meeting public deficit targets. The system comprises a suite of models, with different levels of disaggregation (bottom-up vs top-down; general government vs sub-sectors), which are suitable for the automatic processing of the large amount of monthly/quarterly fiscal data currently published by the Spanish statistical authorities. Our tools are instrumental in the ex-ante detection of risks to official projections, and can thus help reduce the ex-post reputational costs of budgetary slippage. On the basis of our results, we discuss how official monitoring bodies could expand, on one hand, their toolkit to evaluate regular adherence to targets (moving beyond a legalistic approach) and, on the other, their communication policies as regards sources of risks to (ex-ante) compliance with budgetary targets.

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File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/14/Fich/dt1416e.pdf
File Function: First version, July 2014
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Paper provided by Banco de España & Working Papers Homepage in its series Working Papers with number 1416.

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Length: 42 pages
Date of creation: Jul 2014
Handle: RePEc:bde:wpaper:1416
Contact details of provider: Web page: http://www.bde.es/

Web page: http://www.bde.es/bde/en/secciones/informes/Publicaciones_se/docs/
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  1. Merola, Rossana & Pérez, Javier J., 2013. "Fiscal forecast errors: Governments versus independent agencies?," European Journal of Political Economy, Elsevier, vol. 32(C), pages 285-299.
  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. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
  4. Pina, Álvaro M. & Venes, Nuno M., 2011. "The political economy of EDP fiscal forecasts: An empirical assessment," European Journal of Political Economy, Elsevier, vol. 27(3), pages 534-546, September.
  5. Michael Artis & Massimiliano Marcellino, 2001. "Fiscal forecasting: The track record of the IMF, OECD and EC," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 20-36.
  6. Jeffrey Frankel & Jesse Schreger, 2013. "Over-optimistic official forecasts and fiscal rules in the eurozone," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 149(2), pages 247-272, June.
  7. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non-linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300.
  8. Filippo Moauro & Giovanni Savio, 2005. "Temporal disaggregation using multivariate structural time series models," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 214-234, 07.
  9. Joan Paredes & Diego J. Pedregal & Javier J. Pérez, 2009. "A quarterly fiscal database for the euro area based on intra-annual fiscal information," Working Papers 0935, Banco de España;Working Papers Homepage.
  10. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
  11. Gomez, Nicolas & Guerrero, Victor M., 2006. "Restricted forecasting with VAR models: An analysis of a test for joint compatibility between restrictions and forecasts," International Journal of Forecasting, Elsevier, vol. 22(4), pages 751-770.
  12. 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.
  13. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
  14. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
  15. John Clark & Caroline Gibbons & Susan Morrissey & Joshua Pooley & Emily Pye & Rhett Wilcox & Luke Willard, 2013. "Estimates of uncertainty around budget forecasts," Treasury Working Papers 2013-04, The Treasury, Australian Government, revised Nov 2013.
  16. International Monetary Fund, 2005. "Fiscal Transparency and Economic Outcomes," IMF Working Papers 05/225, International Monetary Fund.
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