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Posted: April 20th, 2022
One method is a simple time-series extrapolation or regression against time.
One method is a simple time-series extrapolation or regression against time. These extrapolations may be by:
One method is a simple time-series extrapolation or regression against time. These extrapolations may be by
(1) constant increments (collections increased by $5,000 in each of the last five years, so they are estimated to increase by $5,000 this year);
(2) constant percentage change (collections increased by 5 percent in each of the last five years, so they are estimated to increase by 5 percent this year);
(3) simple growth models using the average annual compounding formula developed in Chapter 4; and
(4) linear or nonlinear time trends in which revenue for the budget year is estimated as an arithmetic function of time (R a bt) or as a logarithmic function of time (lnR a bt), where R equals collections from the revenue source and t equals a time index, choosing between the trends according to which is judged most likely to produce a reasonable estimate.
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A simple time-series extrapolation or regression against time is one method. These extrapolations could be made by:
A simple time-series extrapolation or regression against time is one method. These extrapolations could be made by
(1) constant increments (collections increased by $5,000 in each of the previous five years and are expected to increase by $5,000 this year);
(2) constant percentage change (collections have increased by 5% in each of the last five years, and are expected to increase by 5% this year);
(3) simple growth models based on the formula for average annual compounding developed in Chapter 4; and
(4) linear or nonlinear time trends in which revenue for the fiscal year is estimated as an arithmetic function of time (R a bt) or as a function of time (R a bt).
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