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Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank

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Author Info

  • Alberto Cabrero

    ()
    (Banco de España)

  • Gonzalo Camba-Mendez

    ()
    (European Central Bank)

  • Astrid Hirsch

    ()
    (European Central Bank)

  • Fernando Nieto

    ()
    (Banco de España)

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    Abstract

    The main focus of this paper is to model the daily series of banknotes in circulation in the context of the liquidity management of the Eurosystem. The series of banknotes in circulation displays very marked seasonal patterns. T o the best of our knowledge the empirical performance of tw o competing approaches to model seasonality in daily time series, namely the ARIMA-based approach and the Structural Time Series approach, has never been put to the test. The application presented in this paper provides valid intuition on the merits of eac happroach. The forecasting performance of the models is also assessed in the context of their impact on the liquidity management of the Eurosystem.

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    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/02/Fic/dt0211e.pdf
    File Function: First version, May 2002
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    Bibliographic Info

    Paper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 0211.

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    Length: 44 pages
    Date of creation: May 2002
    Date of revision:
    Handle: RePEc:bde:wpaper:0211

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    Web page: http://www.bde.es/
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    Related research

    Keywords: Daily Forecast; Liquidity Management; ARIMA modelling; State Space modelling; Seasonality; Cubic Splines;

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    References

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    1. Siem Jan Koopman & Marius Ooms, 2001. "Time Series Modelling of Daily Tax Revenues," Tinbergen Institute Discussion Papers 01-032/4, Tinbergen Institute.
    2. Pierce, David A & Grupe, Michael R & Cleveland, William P, 1984. "Seasonal Adjustment of the Weekly Monetary Aggregates: A Model-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 260-70, July.
    3. Harvey, Andrew & Koopman, Siem Jan & Riani, Marco, 1997. "The Modeling and Seasonal Adjustment of Weekly Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 354-68, July.
    4. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    5. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
    7. Bindseil, Ulrich & Seitz, Franz, 2001. "The supply and demand for Eurosystem deposits - The first 18 months," Working Paper Series 0044, European Central Bank.
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    Cited by:
    1. Bindseil, Ulrich & Nyborg, Kjell G., 2007. "Monetary policy implementation: A European Perspective," Discussion Papers 2007/10, Department of Business and Management Science, Norwegian School of Economics.
    2. Diego Elías & Matías Vicens, 2012. "Bills and Coins Daily Demand Forecast," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(65-66), pages 23-39, September.
    3. Bindseil, Ulrich & Camba-Mendez, Gonzalo & Hirsch, Astrid & Weller, Benedict, 2006. "Excess reserves and the implementation of monetary policy of the ECB," Journal of Policy Modeling, Elsevier, vol. 28(5), pages 491-510, July.
    4. Fischer, Björn & Köhler, Petra & Seitz, Franz, 2004. "The demand for euro area currencies: past, present and future," Working Paper Series 0330, European Central Bank.

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