Reference no: EM133002298

BUSA3015 Business Forecasting - Macquarie University

Case Study Report 1

You have been employed as a consultant for a joint project by the Labour force Association of Australia and the Australian Government Treasury.

As part of your role in the Business Analytics and Data Analytics team, you have been asked to forecast total employment (i.e. total employed), as part of a wider report being commissioned by the above collaboration - on Australia's Labour Force Status.

Questions

• Obtain the ABS statistics for Labour Force - 6202001
• Download Table 1.
• For the purposes of this report you are to consider the Total Employed Labour Force data. There are three series in Table 1: Original, Seasonally-adjusted, and Trend (please choose carefully throughout this report!)
• For the purposes of this report, only consider the data from August 2011 to July 2020 as the sample of data that is available to you - that is, ignore any recent observations.
• This means that the first actual observation in your Excel file is from August 2011 and your last actual observation in your Excel file is from July 2020.
• Use Excel and no other statistical software for the purposes of this report.
• You may use Minitab for constructing correlograms.

Exercise 1 - Application

For the purposes of this report, only consider the data from August 2011 to July 2020 as the sample of data that is available to you - that is, ignore any recent observations.

This means that the first actual observation in your Excel file is from August 2011 and your last actual observation in your Excel file is from July 2020.

For the Seasonally-adjusted data for the Employed total (Series ID: A84423043C) available in Table 1: Forecast the out-of-sample values for every month in the period August 2020 - July 2021 (both months inclusive) using Holt's Exponential Smoothing with the following parameters: alpha = 0.5 and beta = 0.3. For the seed of the level use the first observation, Y1. For the seed of the trend - use the formula [(Y3 - Y1)/2] or [(Y2 - Y1) + (Y3 - Y2)/2] they will give the same answer.

Before you begin Exercise 1, let's check that you have the right data! The average should be 11977.9!

Once you perform Holt's Exponential Smoothing with alpha = 0.5 and beta = 0.3, what are the following numerical values:
1. The within-sample forecast for April 2020.
2. The out-of-sample forecast for October 2020.
3. The out-of-sample forecast for July 2021.
4. The MSE.
5. The MAPE.

Critically think for a way to optimise alpha and beta via the MSE, and report the following values after your optimisation:
6. Alpha
7. Beta
8. The MSE
9. The out-of-sample forecast for October 2020.
10. The out-of-sample forecast for July 2021.

Exercise 2 - Application

For the purposes of this report, only consider the data from August 2011 to July 2020 as the sample of data that is available to you - that is, ignore any recent observations.

This means that the first actual observation in your Excel file is from August 2011 and your last actual observation in your Excel file is from July 2020.

For the Original data for the Employed total (Series ID: A84423085A) available in Table 1: Forecast the out-of-sample values for every month in the period August 2020 - July 2021 (both months inclusive) using Winter's Exponential Smoothing (Multiplicative) with the following parameters: alpha = 0.5, beta = 0.3, and gamma = 0.2. For the seeds of the level, trend, and seasonal components - utilise the methods described and discussed in class.

Before you begin Exercise 2, let's check that you have the right data! The average should be 11983.7!

Once you perform Winters Exponential Smoothing with alpha = 0.5, beta = 0.3, and gamma = 0.2, what are the following numerical values:
11. The seasonal component for June 2020.
12. The within-sample forecast for April 2020.
13. The out-of-sample forecast for July 2021.
14. The MSE.
15. The MAPE.

Critically think for a way to optimise alpha, beta, and gamma via the MSE, and report the following values after your optimisation:
16. Alpha
17. Gamma
18. The MSE
19. The within-sample forecast for April 2020.
20. The out-of-sample forecast for July 2021.

Exercise 3

800 words (+/- 10%) not counting labels and numbers on graphs AND no more than three A4 sheets in portrait/vertical mode (use the template DOC file provided on iLearn):

Your Exercise 3 responses should refer mostly to Exercise 2 (you may refer to exercise 1 in some of your comments)

For the model in Exercise 2 (i.e., WES), given that you have the actual data for the out-of-sample period (you considered the within-sample period to end in July 2020 - but you do have data for August 2020 and onwards) - discuss your forecasting method, your forecasts, and the employment insights from these, using the following steps:

• Attribution
• Scope
• Application
• Analysis
• Articulation of Issues
• Critique
• Position

You must use the above steps as sub-headings in your response. Failure to do so will result in a loss of marks.

Note in the rubric on iLearn - "sources" are from within the assignment including your own sources of generated results. You do not need to cite the materials provided via iLearn. Given the nature of this task, you will not be penalised for not referring to other sources (although other sources may give you unique insights for your responses).

Attachment:- Business Forecasting.rar