Instructions (adapted from Hanke and Wichern) (Page limit is 15 pages)

Australian Bureau of Statistics (ABS) provides retail data for different groups and different states as well as the aggregate numbers. The main webpage to access the retail statistics is:

http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/8501.0Jun%202013?OpenDocument

On the ‘Downloads’ tab you will find data for different categories. Table 11“ Retail Turnover, State by Industry Subgroup, Original” contains the data you can use in this part. You can select the state and the group you wish to analyse or you can use the aggregated data.The file contains monthly retail turnover data from April, 1982 to June, 2013. You are hired as a forecasting consultant to analyse the retail data as there is a concern that Australia retail sector is bad shape:

http://www.abc.net.au/news/2013-08-05/retail-sales-flat-in-june/4865264

You, as an econometrics expert, need to analyse, generate and assess forecasts for monthly sales retail turnover for the rest of 2013.

After consulting with your peers, you decide to consider three models/methods for applicationto this dataset to generate forecasts.

Models/Methods USING SAS AND/ OR EXCEL:

A) Naive
B) Decomposition (multiplicative model)
C) A model of your choice**.

• Perform an exploratory analysis on the entire dataset and discuss the important aspects of the data. Show all RELEVANT output (e.g. graphs, tables).
• Choose a suitable decomposition model for model B while clearly motivating your choiceusing your answer in part (i) and any other relevant information i.e. choose between a multiplicative OR an additive model.
• Choose a suitable model C while again clearly motivating your choice*.
• Clearly present and discuss the trend-cycle, seasonal and error components in the in-sample data, as assessed by model B.Contrast these components between the models B and C if appropriate.
• Choose a model form forthe trend component (one for Model B and also for model C, but only if appropriate) and clearly and properly justify your choice.
• Discuss and compare how well, or otherwise,the models A, B (including trend as in (v)) and C fit the data in the in-sample period. Use statistical tests if appropriate.
• Forecast the hold-out year, of monthly turnover data using Models A-C, using only the chosen in-sample period. Provide a table of these forecasts as well as a graph, together with the actual turnover for the last 12 months.
• Assess the accuracy of each model and compare the models for forecast performance in the appropriate ways.Identify the best forecasting model and why you chose it as best.
• Discuss why you think the ‘best’ model beat the other two models AND/OR why there was (or wasn’t) any disagreement between forecast accuracy measures.
• Provide 95% interval forecasts for sales in the last 12 month for each model. Clearly present the method you used to obtain such interval estimates. As much as you can, discuss, interpret and compare these intervals.Are they accurate? Is one model better than the others here?
• Choose a forecast model from A-C, motivating your choice. Then, update it with the latest available data, and then generate both point and 95% interval forecasts for the rest of 2013.Present these in an appropriate manner. Further, discuss how accurate you think these 2013 forecasts might turn out to be, with justification.
• Prepare an executive summary outlining and summarising your analysis, providing your forecasts in a form suitable for the evening news. Use layman’s terms, since the majority of the viewers did not take the advanced forecasting course and do not understand statistical notation.
• prepare up to a 0.5 pagestatement outlining the state of retail sector in Australia and your expectations for the rest of 2013.prepare this like a certified statement from an expert to the governor of the Reserve Bank of Australia (RBA), so it can be used next time when RBA makes a decision on interest rates.