ECO220Y5: Introduction to Data Analysis & Applied Econometrics
Data Project Two
F/W 2023/24
1 Is there a bubble in the Toronto real estate market? Does the data
support the idea Toronto real estate might be heading for a crash?
1.1 Project Overview
Your goal is to describe some of the variables that might indicate risks facing the Toronto real estate sector. You should comment on the articles which discuss the severity of the situation for Toronto real estate both in relative and absolute terms. You will do this using the same ‘project- data Summer2021.xlsx’ file provided. Continuing from your previous analysis you will produce addi- tional evidence using your knowledge from linear regression. You must now include and discuss results using multivariate regression techniques, for example: output tables, interpretation of coefficients, goodness of fit statistics, plots of residuals, etc. You should consider carefully the best specification and provide evidence (formal testing or analysis of plots) to support your model selection. You should consider creating indicator variables that might be used to impact the intercept or as interaction terms. You should look for common violations of the OLS assumptions in your re- gressions such as heteroskedasticity, serial correlation and non-normality. You should conclude using your model to determine whether there is currently a bubble in the Toronto real estate market. You should comment on how significant your variables of interest will be impacted in the future by the bubble and if you think there is likely a crash coming in the key variables.
As with data project one, the data is a set of variables downloaded and combined from the MLS database, Statistics Canada, Equifax and the CMHC database. It comprises monthly time series data for Toronto and a few other cities or Canada as a whole. A brief description of the available variables is available in the excel file under the description tab (further description is available on the corresponding websites). Using suitable quantitative techniques from ECO220 describe some interesting characteristics of the variables you decide to focus on. In interpreting, explaining and assessing the validity of your output, you should read the articles provided. Try to pick out variables that might be related in some way to the question and discuss these. You can also search out your own literature to guide your discussion but be sure to include any other sources in a bibliography.. Avoid using any outside data as the goal of the project is to make your case using data analysis on the data you have been provided.
1.2 Project Submission
As with project 1, project 2 will not be marked based on length but rather how well you addressed the question. Your submission should not exceed 1200 words of text and 4 pages of graphs and tables. If it is written in a clear and concise style, and you have a good handle on generating useful graphs, this limit will be sufficient for a full mark. Write an assessment that is smart, not long. Highlight the findings that are puzzling, practically useful, thought provoking or seem to be counter-intuitive. Try to deliver a submission that is interesting and easy to follow, a short piece of statistical analysis that you yourself would like to read.
This Data Project is worth 7.5% of your final mark. All statistical analysis should be done using Stata. The final report should be submitted as a single written document in .pdf format and you must also include your DO file for Stata or SCRIPT file for R. The submission deadline is Friday April 5th.
1.3 Software Help
Several videos on how to use econometrics software are available online. An additional help lecture will be provided. Alternatively there are some good handbooks available for Stata.