Modeling and Forecasting Currency in Circulation in Sri Lanka
Deputy Director of the Domestic Operations Department of the Central Bank of Sri Lanka, LK
Mrs. Rupa Dheerasinghe is a Deputy Director of the Domestic Operations Department of the Central Bank of Sri Lanka. She received a B.A. Degree in Economics from the University of Peradeniya, a Post Graduate Diploma in Applied Statistics from the University of Colombo and a M.A. Degree in Economics from the Monash University, Australia. Her research interests are in International Trade and Monetary Policy.
Currency in circulation is typically estimated either by specifying a currency demand equation based on the theory of transaction and portfolio demand for money or univariate time series models. The first approach works well with low frequency data but faces limitations with high frequency data series. Therefore, this paper proposes an alternative approach in modeling the high frequency data series by decomposing the trend, the seasonal, and the cyclical components. Three separate models were estimated with monthly, weekly and daily time series, assembling tools for forecasting trend, seasonal patterns and cycles in individual series separately. Trend and seasonal effects were identified by regressing on trend and seasonal dummies while cyclical dynamics were captured by allowing for ARMA effect in the regression disturbances. The sample period is 1 January 2000 to 31 August 2005 and data for 1 September 2005 to 31 January 2006 were used for post validity test. All three models fit the data well and provide very close forecasts during the post sample period. All three models clearly identify both inter-month and intramonths variations of currency in circulation. The models also identified that the Sinhala/Tamil New Year, elections, Christmas and the day prior to public and bank holidays have significant positive impact on demand for currency in Sri Lanka. This methodology may be used in forecasting currency in circulation with careful assessment of day to day current developments in the economy.