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Should quarterly government finance statistics be used for fiscal surveillance in Europe?

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  • Pedregal, Diego J.
  • Pérez, Javier J.

Abstract

We use a newly available dataset of euro area quarterly national accounts fiscal data and construct multivariate state space mixed-frequencies models for the government deficit, revenue and expenditure in order to assess its information content and potential use for fiscal forecasting and monitoring purposes. The models are estimated using annual and quarterly national accounts fiscal data, but also incorporate monthly information taken from the cash accounts of the governments. The results show the usefulness of our approach for real-time fiscal policy surveillance in Europe, given the current policy framework in which the relevant official figures are expressed in annual terms.

Suggested Citation

  • Pedregal, Diego J. & Pérez, Javier J., 2010. "Should quarterly government finance statistics be used for fiscal surveillance in Europe?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 794-807, October.
  • Handle: RePEc:eee:intfor:v:26:y::i:4:p:794-807
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    Cited by:

    1. Stylianos Asimakopoulos & Joan Paredes & Thomas Warmedinger, 2020. "Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(1), pages 369-390, January.
    2. Teresa Leal & Javier J. Pérez & Mika Tujula & Jean-Pierre Vidal, 2008. "Fiscal Forecasting: Lessons from the Literature and Challenges," Fiscal Studies, Institute for Fiscal Studies, vol. 29(3), pages 347-386, September.
    3. Carlos Barros & Luis Gil-Alana, 2013. "Inflation Forecasting in Angola: A Fractional Approach," African Development Review, African Development Bank, vol. 25(1), pages 91-104.
    4. Laura Carabotta & Peter Claeys, 2024. "Combine to compete: Improving fiscal forecast accuracy over time," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 948-982, July.
    5. Robert Ambrisko, 2022. "Nowcasting Macroeconomic Variables Using High-Frequency Fiscal Data," Working Papers 2022/5, Czech National Bank.
    6. Bańkowski, Krzysztof & Faria, Thomas & Schall, Robert, 2022. "How well-behaved are revisions to quarterly fiscal data in the euro area?," Working Paper Series 2676, European Central Bank.
    7. Giuseppe Bianchi & Tatiana Cesaroni & Ottavio Ricchi, 2015. "ISBEM: An econometric model for the Italian State Budget Expenditures," Working Papers LuissLab 15120, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    8. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    9. Lahiri, Kajal & Yang, Cheng, 2022. "Boosting tax revenues with mixed-frequency data in the aftermath of COVID-19: The case of New York," International Journal of Forecasting, Elsevier, vol. 38(2), pages 545-566.
    10. 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.
    11. Joan Paredes & Javier J. Pérez & Gabriel Perez Quiros, 2023. "Fiscal targets. A guide to forecasters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 472-492, June.
    12. Giuseppe Bianchi & Tatiana Cesaroni & Ottavio Ricchi, 2013. "Previsioni delle spese del bilancio dello Stato attraverso i flussi di contabilità finanziaria," Rivista di Politica Economica, SIPI Spa, issue 1, pages 271-326, January-M.
    13. Paredes, Joan & Pedregal, Diego J. & Pérez, Javier J., 2014. "Fiscal policy analysis in the euro area: Expanding the toolkit," Journal of Policy Modeling, Elsevier, vol. 36(5), pages 800-823.
    14. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española / Review of Public Economics, IEF, vol. 211(4), pages 117-146, December.
    15. Ghysels, Eric & Ozkan, Nazire, 2015. "Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1009-1020.
    16. Carabotta, Laura & Paluzie, Elisenda & Ramos, Raul, 2017. "Does fiscal responsibility matter? Evidence from public and private forecasters in Italy," International Journal of Forecasting, Elsevier, vol. 33(3), pages 694-706.
    17. Andrew Hughes Hallett & Moritz Kuhn & Thomas Warmedinger, 2012. "The gains from early intervention in Europe: Fiscal surveillance and fiscal planning using cash data," European Journal of Government and Economics, Europa Grande, vol. 1(1), pages 44-65, June.
    18. Francisco de Castro & Francisco Martí & Antonio Montesinos & Javier J. Pérez & Antonio Jesús Sánchez Fuentes, 2018. "A Quarterly Fiscal Database Fit for Macroeconomic Analysis," Hacienda Pública Española / Review of Public Economics, IEF, vol. 224(1), pages 139-155, March.
    19. 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 / Review of Public Economics, IEF, vol. 190(3), pages 27-58, June.
    20. Alberto Urtasun & Mara Gil & Javier J. Perez, 2017. "Nowcasting private consumption: traditional indicators, uncertainty measures, and the role of internet search query data," EcoMod2017 10745, EcoMod.

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    More about this item

    Keywords

    Fiscal policies Mixed frequency data Forecasting Unobserved components models State space Kalman Filter;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E6 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
    • H6 - Public Economics - - National Budget, Deficit, and Debt

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