Bills and Coins Daily Demand Forecast
AbstractAn accurate liquidity forecast is necessary for an effective implementation of monetary policy. Its quality is determined by the quality of its components: the projected demand for bank reserves and of the, so called, autonomous monetary factors, such as the demand for bills and coins of the public, the monetary effect of public sector and external sector operations, and some operations with the financial sector. The objective of the paper is to improve one component of this process, the daily forecast of the short term demand for bills and coins. Therefore, two models, that treat calendar effects, business day effects, and annual and monthly seasonal effects, were estimated. Both showed a good short-term forecasting performance.
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Bibliographic InfoArticle provided by Central Bank of Argentina, Economic Research Department in its journal Ensayos Económicos.
Volume (Year): 1 (2012)
Issue (Month): 65-66 (September)
bills and coins demand; daily projections; forecasting; monetary policy;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E41 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Demand for Money
- E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Clements,Michael & Hendry,David, 1998.
"Forecasting Economic Time Series,"
Cambridge University Press, number 9780521632423.
- Alberto Cabrero & Gonzalo Camba-Mendez & Astrid Hirsch & Fernando Nieto, 2002. "Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank," Banco de Espaï¿½a Working Papers 0211, Banco de Espa�a.
- 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.
- 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.
- Cabrero, Alberto & Camba-Méndez, Gonzalo & Hirsch, Astrid & Nieto, Fernando, 2002. "Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank," Working Paper Series 0142, European Central Bank.
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