Your project requires you to
• Develop a linear multiple regression model using the sales data for an 18-month sample (July 2013 through December 2014) period but excluding the latest 6 months (All 2015 sales). Your model should include suitable dummy variables and transformations for independent variables where appropriate. This is the most important step and needs considerable thought.
• Evaluate your model against other potential specifications.
• Develop a second model based on a log-linear model. This typically uses the same independent variables as the first model, but you may need to make independent variable transformations as well.
• Test the model using sales from the latest quarter (April this year through June this year) and specifically report statistics such as MAPE, FSD, Mean and Median A/S ratio, and charts showing the distribution of A/S ratios.
• Decide which of the two models is superior (linear or log-linear) and argue whether your model would produce assessment estimates that would be within benchmark figures.
The data covers one Adelaide Local Government Area (LGA) but your task is to deal with one of the sub-markets that have been defined. For convenience we have define sub-markets by suburb name or two suburbs grouped together.
For 2015 the Data is in the Local Government Area (LGA) of Marion and your location options for sub-markets are as follows:
Each data point represents one transaction (comparable sale) of a property in the LGA. The data is derived from the South Australian Government – Office of the Valuer General and Lands Titles Office. You should create two separate data sets (Model and Test as indicated above) that relate to your specific submarket.
• The two models should be created using data from July 2013 through December 2014 (Model data set). Data after this period should NOT be included in the model but “held out” for accuracy testing (see below).
• Data from 2015 is to be used to test the model for estimation accuracy (Test data set).
The data is available as an Excel spreadsheet from this link. Some of the data is coded and information about these codes is provided separately from this link. You do not need to use all the variables in your analysis as some of it is only descriptive.
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