Policy Memo; Kelsey City Forecast of the Major Sources of Kelsey’s Tax Revenue for the Upcoming Year
Kelsey City Council
Policy Memo
To: The Kelsey City Council
Subject: Forecast of the major sources of Kelsey’s tax revenue for the upcoming year.
Date: 16th December, 2013
The Director of Budget and Finance requested me to prepare a policy memo and a presentation to the Kelsey City Council to explain and forecast the major sources of Kelsey’s tax revenue for the upcoming year. This is a city in the Northwest Valley. It is found in an interesting place; in the hills. Currently, statistics show that the city has about 650,000 people. The city is known to be very good in offering services which are only found in big cities, but nit has the aura of a small City. This makes it very interesting to live in.
The city has various sources of tax revenue. The year 2005 is in focus in terms of the tax revenue obtained. This will help in making a prediction of the next years’ levels of tax revenue
Financial Performance for the year ended 30th June, 2005
For the year ended 30th June, 2005, Kelsey City was able to get 1.3billion in revenue. This was acquired with a population of about 623,000 residents.
Correlation
It is important to understand the concept of correlation. This is a technique which tries to explain the relationship between two variables. This analysis technique uses more than one input, since it is used in measuring the relationship between two or more inputs. To achieve this, there is need to obtain the correlation coefficient.
Covariance
This is usually the measure of the way two variables are related. The covariance in variables is either in dependent or independent variables. Covariance is very useful in measuring the side the relationship is moving towards as well as how strong it is. The direction may be positive, and it is brought by having one variable increase as the other one. This creates a positive direction of the covariance. Secondly, the covariance may be negative. This is created by having one variable decrease, while the other one goes down.
Correlation Coefficient
This results from standardization of the covariance. This is usually derived by dividing the covariance by the standard deviation product for the two variables. The correlation may be +1 or –1 between the variables. A +ve correlation indicates that the variables are having a perfect correlate; while a –ve one indicates that the variables are having a perfect negative correlation.
Regression analysis
Regression analysis is applied by measuring the relationship between two variables: whether independent or depended (Sen & Srivastava, 1990). For example, in the case of the Kelsey city, the tax revenue is the dependent value. The sales of the city depend wholly on the population involved in moving the operations.
The sales for the year b2006 will go up. This will be more than the sales of the year 2005. This will depend on the movement of the number of people carrying out their operations in Kelsey City.
The regression path takes the following equation
Y=bx+a
Y stands for the variable that we would like to obtain its forecast. ‘b’ represents the slope the regression while x stands for the independent variable. In the case of Kelsey City, y will be represented by the amount of tax revenue while x will be represented by the population of the city. ‘a’ represents the value of the dependent variable in our case the tax revenue for Kelsey City while the independent variable is nil.
Regression analysis objectives
Regression has the objective of showing the relationship between two or more variables. It is able to give reliable forecasts.
Forecast for the coming year
Inputs
In the forecasting of next year’s tax revenue amounts, the population and 2005 level of tax revenue is useful. The population is the independent variable while the tax revenue is the dependent variable.
In the case of Kelsey City, a +1 change in the population of the City will lead to a +1 change in the sources of revenue for the City. If the population of the City shows a -1 change, the sources of tax revenue for the City will reduce by that margin since they would be perfectly negatively correlated.
In the case of Kelsey City, the population of the City has a 4.30% increase. Remember this is the independent variable. Therefore, the tax revenue received by the City will have to change in the same rate. This means that from the year 2005, the next year’s income obtained by the City of Kelsey will increase by 4.33%.
As indicated in the table below, the tax revenue will be higher.
The amounts are in millions.
| Year | Tax Revenue Amount(millions) | Population Change | |
| 2005 | 1300 | 4.30% | |
| 2006 | 1355.9 |
Description of the forecast
The forecast indicates that the City will be able to carry out more development projects. This is because the revenue obtained will be higher in the coming year.
Notes to the analysis
- Statements regarding the analysis
Any slight decrease in the city’s population will have a big negative impact on the level of tax revenue
- Reasons for the statements
The above statement is true since the population and tax revenue have a linear perfect correlation
Conclusion
It is important to note that the relationship between variables in an analysis is very important. This is the case in the Kelsey City analysis. With the population of the City going up, the tax revenue would go up from the level witnessed in the year 2005. This means that the City can be able to budget for more things since a higher level of income would be obtained in the next years from 2005. The rate at which the revenues are growing shows a perfect correlation with the population of the city.
Reference
Sen, A. & Srivastava, M. (1990). Regression Analysis: Theory, Methods and Applications. Springer.
