Graphing and interpreting errors in Budget Forecasting - Solutions

Part 1: Budget forecasting errors over time

Errors in Budget forecasting are often represented as a percentage of the total economic output of a country, or gross domestic product (GDP). This is a more realistic measure of the size of a Budget forecasting error as it is relative to the size of an economy. The errors in Budget forecasting represented as a percentage of GDP are shown in the table below.

Errors for One-Year Forecasts, as a Percentage of GDP, 2011–2022

Year ending 30 June	Budget outcome as % of GDP	Error in forecasts as % of GDP
2011	-3.3	-0.4
2012	-2.9	-1.4
2013	-1.2	-1.3
2014	-3.0	-1.9
2015	-2.3	-0.5
2016	-2.4	-0.3
2017	-1.9	-0.3
2018	-0.6	1
2019	0.0	-0.8
2020	-4.3	-4.7
2021	-6.5	4.5
2022	-1.4	3.6

Graph the Budget outcomes and errors in percentage forecasts for the period between 2010-2022 on one chart.
What type of graph did you select to use? Line graph
Why did you choose this type of graph? To compare the trend between the budget outcome and error in forecasts easily.
Interpret the graph and write a paragraph describing your interpretation using the following framework. Student responses will vary.

Framework for interpreting graphs

Framework for interpreting graphs - Image

Part 2 – Distribution of Budget forecasting errors

Open a spreadsheet and put the percentage errors in a table with the following headings.

	Percentage error
	-4.7
	-1.9
	-1.4
	-1.3
	-0.8
	-0.5
	-0.4
	-0.3
	0.3
	1
	3.6
	4.5
Average (mean)	-0.2
Median	-0.4

Use the SORT function to sort the percentage errors from lowest to highest.
Set up formulas to calculate the average (mean) and another to calculate the median.
What is the average percentage error? -0.2 What is the median percentage error? -0.4
Are these figures similar? Which one is higher and why? The mean is higher than the median making the data positively skewed because there were more negative values in the data set.
On the same spreadsheet (you should have a bit of space to the right of your first table) set up another table.
Count the number of percentage errors in each category and add this information to the table. The -2 to -1 range has been done for you.

Put in a formula at the bottom of the column to add up the number of percentage errors you have. If the Total is not 12, check the information you’ve entered.

Category	Number of errors in this category
-5 to -4	1
-4 to -3	0
-3 to -2	0
-2 to -1	3
-1 to 0	4
0 to 1	1
1 to 2	1
2 to 3	0
3 to 4	1
4 to 5	1
Total	12

Insert a chart to display this information. Choose your style and colours. Make sure the chart has labels and a title. Refer to Building charts and tables – How-to-sheet.
Describe the overall pattern of the data (shape, center, spread), and any deviations from the pattern (outliers). If necessary, use the framework provided above. There is a positive skew to the data. The mean and median are located in the same category.

Linked activity:

The Budget and forecasting (AC v9.0)