Thesis and Appendix

If this is your first time visiting my site, please take the time to read my Masters Research Paper and its Appendix.

The latter is more of a demonstration of the bulk of the R code I used to conduct my analysis.

My project used a hedonic regression model to establish a connection between real estate prices in the Canadian census metropolitan area market, and air pollutant concentrations (particularly with PM_2.5).

Due there already being extensive research and literature on hedonic regression models, I sought to take a more novel approach compared to previous endeavours.

First, using an instrumental-variable (IV) approach in a panel-data context. The instrumental variables used were Wind Speed and Wind Direction, though only Wind Speed being used in the end due to rejecting the Sargan test.

Second, utilizing temporal disaggregation to turn several variables from Statistics Canada that were only available at an annual frequency, down to a monthly frequency.

Most of the analysis used for this project was done in R, with the first half of the Appendix vignette focusing on the more “data science-y” aspects of the project; incorporating and using packages from the Tidyverse.

This was a huge project for me as it taught me the bulk of the core R programming skills that I now have.

If you find either my Thesis or its Appendix insightful or worthy of sharing, please leave me a comment or share with your peers!

Thanks for reading.