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Procedure for Procedure for Forecasting with Forecasting with Time Series DataTime Series Data
Identification ofIdentification ofvariable of interestvariable of interest
Identification of differentIdentification of differentforecasting methodologiesforecasting methodologies
Estimation of modelEstimation of model
Calculation of forecastCalculation of forecastaccuracy and finalaccuracy and final
model selectionmodel selection
Generation of forecastsGeneration of forecasts
Reexamination of forecastingReexamination of forecastingaccuracy at a later timeaccuracy at a later time
Reexamination of presentReexamination of presentmodel or possible considerationmodel or possible considerationof alternate forecasting modelsof alternate forecasting models
Model selectionModel selectionand forecastingand forecasting
This technique uses all the preceding This technique uses all the preceding observations to determine a smoothed observations to determine a smoothed value for a particular time periodvalue for a particular time period
SStt = smoothed value for time period, = smoothed value for time period, tt
= = AyAytt + (1 -+ (1 - A A))SStt-1-1 t t = 2, 3, 4, ...= 2, 3, 4, ...
Linear Exponential Linear Exponential SmoothingSmoothing
Procedure 2Procedure 2Use the first five years to estimate the Use the first five years to estimate the initial trendinitial trend
Procedure 1Procedure 1Let bLet b11 = 0= 0 provided you have a large provided you have a large
number of years, this procedure provides number of years, this procedure provides an adequate initial estimate for the trendan adequate initial estimate for the trend
Procedures for Summarizing the ResultsProcedures for Summarizing the Results
Forecasting Using Linear Forecasting Using Linear and Seasonal Exponential and Seasonal Exponential
SmoothingSmoothing
Procedure 1:Procedure 1:
3.3. Set the initial smoothed value for quarter Set the initial smoothed value for quarter 44 ((SS00) ) equal to the actual value for equal to the actual value for
quarter quarter 4 (4 (t t + 1)+ 1)
2.2. Set the initial trend estimate Set the initial trend estimate ((bb00)) equal to equal to 00
1.1. Set the initial seasonal factors equal to Set the initial seasonal factors equal to 11
Forecasting Using Linear Forecasting Using Linear and Seasonal Exponential and Seasonal Exponential
SmoothingSmoothingProcedure 2:Procedure 2:
3.3. The initial smoothed value for quarter 4, The initial smoothed value for quarter 4, SS00,, is the forecast value for each of the 4 is the forecast value for each of the 4
quarters in year t quarters in year t + 1+ 1
2. 2. Deseasonalize the data for the first two Deseasonalize the data for the first two years and calculate the least squares line years and calculate the least squares line through these deseasonalized values, dthrough these deseasonalized values, dtt
1.1. Use the first two years of data to determine Use the first two years of data to determine the seasonal indexesthe seasonal indexes
Choosing the Appropriate Choosing the Appropriate Forecasting ProcedureForecasting Procedure
Exponential smoothing procedures are excellent Exponential smoothing procedures are excellent for short-term forecasts, whereas the component for short-term forecasts, whereas the component decomposition is useful for medium- and long-decomposition is useful for medium- and long-range forecastingrange forecasting
Short term forecast: one to three months Short term forecast: one to three months Medium-range forecast: four months to Medium-range forecast: four months to
two yearstwo years Long-range forecast: two or more yearsLong-range forecast: two or more years