Who Forms Better Expectation on House Price?
The data you need is “Expected Change in Home Values During the Next Year” by the categories of age, income, education, and gender, respectively. Choose the sample data from March 2007 to June 2015. It means you will need to retrieve 4 data files, one for each category.
By clicking the link above, you will be directed to the UMichigan’s Survey page. Click “Chart” and then click the category you need. Then scroll down to “Home Buying and Selling Conditions” and locate “Expected Change in Home Values During the Next Year”. It is series 46. Then choose “Excel” file for the “last 50 years”. Save the data file and choose the data range required.
The data series you need is the ” S&P/Case-Shiller U.S. National Home Price Index”, “Seasonally Adjusted”. Choose the sample data from March 2007 to present. Calculate the one-year-forward home price change (price change) for the sample date from March 2007 to June 2015. They are one-year-forward (or 12-month-forward) percentage changes of S&P Case Shiller Home Price Index.
You are encouraged to calculate the forward home price change by yourself. But if you don’t want to get your hands dirty, I already upload the one-year-forward home price change at the attachment, the file name it’s “Forward House Price Change”.
Values During the Next Year” by “age” and one-year-forward house price change should be plotted in one chart. Therefore, you should have 4 charts in total.
A sample chart is posted at the attachment, you can compare your chart with the sample chart to see what you need to work on.
You are encouraged to use excel to calculate RMSE (Root-Mean-Square Error), the difference between the expected price change and the one-year-forward home price change. It is a more accurate measure of expectation errors. RMSE is defined as,
where ∆Pex is the time-t expected price change and I f or is the time-t one-year-forward home price tt change.
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