Who Forms Better Expectation on House Price?
- Economics analyzes people’s behaviors. This project is about comparing expectations of house price formed by different groups of people. The population is categorized by age, income, education, and gender. Through this project, you should be able to find which group forms better or more accurate price expectation.
- This is a research project, which means you need to “research the way to work it out”. Per the syllabus, the research report is worth 100 points and 10% of it (10=100*10%) will go to your final grade.
- Pleaseusefontsize11,doublespaces,maximum5 pages.
- Retrieve the data of consumer expectation from the website of University of Michigan Survey of Consumers,
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.
- RetrievethedataofU.S.NationalHomePricefromthewebsiteofFederalReserveBankofSt.Louise, https://fred.stlouisfed.org/release?rid=199.
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”.
- UseExceltogenerateachartforeachdataset(youshouldhave4datasets)togetherwiththeseries of one-year-forward home price change. For example, the data set of “Expected Change in Home
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.
- Visually diagnose each group of people, by age, income, education, and gender, and explain whether their expectation of home price change is close to the actual price change. This step asks you to describe the difference between the “Expected Change in Home Values” by different consumer groups and the actual forward house price change. These differences are the expectation errors of consumers. The larger the difference is, the less accurate consumer expectation is. In your re- port, you need to tell which group of consumers in each category made more or less mistakes than others.
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.