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Assignment 5: Time Series Analysis and Forecasting, Part B (10%)

Completion requirements

To do: Make a submission To do: Receive a grade

To receive full marks, you need to show all your work, including all the software outputs.

The aim of Assignment 5, Part B is to apply time series and regression analysis to a real-world example, based on sample data that you find.

The data for such a case will be secondary data. The expected length of this assignment is 1,000 words. A 250-word abstract is also required.

The data you use as well as a description of the source of the data must be included in an appendix of the assignment and is not part of the required word count.

Research Topic

The research topic for this part of Assignment 5 is forecasting the average price of houses in a city, such as Vancouver or Toronto, or a province, such as BC or Ontario. Begin by doing some preliminary research to see which city or province you prefer based on the availability of data on past prices and on the independent variables you intend to use to forecast future price.

The city or province as well as the independent variables you choose must be approved by your Open Learning Faculty Member. Examples of independent variables that are useful for determining the price of housing include income, population density, cost and availability of suitable land for building houses, regulations and ease of getting permits for density, height limitations, dwelling type (single-family houses versus condos), and zoning (commercial versus residential). Many more independent variables are possible, which you can suggest based on relevance and data availability.

Data

You will need to obtain quarterly data for several years on both house price, i.e., your dependent variable, and the three or four independent variables you choose.

You will compute a seasonal index to deseasonalize your variables before running the multiple regression. You will provide a seasonally adjusted forecast of the future price of houses and a 95% confidence interval of the forecast, and you will perform t tests of the individual regression coefficients as well as an F-test of the estimated regression line.

You can also obtain the data from Thompson Rivers University Library. See the Course Guide for more about the library or visit the library’s Distance, Regional, and Open Learning website.