About three years ago, I moved from the San Francisco Bay Area to Boulder, Colorado. I grew up in a place where purchasing/renting homes, land, and buildings was (and still is!) extremely expensive. In an article published by 24/7 Wall Street, the authors determined that San Francisco and other parts of the Bay Area are reported to be the most expensive areas to live in the entire United States. So, when I moved to Boulder, I was thrilled to live in a place that had a cheaper, more affordable real estate market. I could not have been more misinformed.
According to a study done by “Area Vibes”, the cost of living in Boulder, Colorado is 32% higher than the average of Colorado and 42% higher than our nation’s average. Now even though it is still not nearly as expensive as living in the San Francisco Bay Area, it is still costs a large amount of money to rent/own a place in Boulder County. After I looked into this data, I thought it would be extremely intriguing to do an analysis on the cost of living in Boulder over-time for my Module 5 Assignment. I decided to use the Boulder Assessor’s Property database that was administered to us by Professor Keegan for this particular analysis.
First things first is that I used the sample Python code that was provided to us during Class 30 to read in and then analyze the data.
After all of the data was read into the program, then I could begin my initial analysis. I determined that the files “Sales”, “Buildings”, and “Land” would be the most helpful for my analysis. The first thing that I did was used the SQL inner join function to compile particular and similar columns within these files. After this was done, I wanted to create an initial visualization that would offer me a better understanding of the type of data that I should be searching for/analyzing.
The graph above does not tell me much about trends over time, but I was able to determine what data would be most helpful. Obviously, the points that are in the top 2/3 of the graph are bound to be large accusations of land (like the multiple purchases of the land for the University of Colorado over time). After viewing this, I went back into my SQL program and dropped all property types that I viewed as too large for this particular analysis. After I did this, it became much easier for me to analyze the upward trend of real estate prices overtime. During our peer evaluation during the first week of November, a classmate offered me a great idea to visualize the data using the values by using the year a particular building was built and price that it had sold for.
As you can see from the graph on the left, it has become increasingly more and more expensive to purchase property in the city of Boulder. The price of these properties are increasing linearly over time and indicate that the cost of living in Boulder will only continue to get more expensive as we move in the next decade. Even though it is not uncommon to see this upward trend of cost of living in any particular city, Boulder still seems to be increasing much faster than those of neighboring cities. “Of the 2,722 areas looked at, Boulder ranked 27th with an average list price in the first half of the year of $1,044,656. That places Boulder in the top 1 percent… in Colorado are Castle Rock at $666,859; Evergreen at $661,000; Westminster at $561,762; Denver at $442,575 and Broomfield at $527,809” (Svaldi, 2015). The quote above comes from a 2015 study. As you can imagine, the difference in cost of living has gotten even more drastic over the past five years alone. I found it difficult to use SQL to showcase the change in price in a small number of years so, I decided to search the web to show just how drastically the housing market can change in a small amount of time.
As you can see in the graphic above, there was a clear and steady increase in the real estate sales prices between the short, four year period of 2013–2017. The graphic above comes from a 2016 real estate study from Boulder resident, Bob Gordon. I believe that the infographic above can be used to help us assume that the same trends have occurred over the past three years (2017–2020).
There are a lot of things that I learned from this case study. I have known for sometime now that Boulder is an expensive place to live. But, I would have never thought that the real estate market was in the top 1% of the entire United States. If you had asked me before I had done this assignment, I would have never known that the price of all of these homes/buildings where linearly increasing the way that they currently are. If this were a study that I had an extended period of time to complete (i.e. multiple months), then I would have liked to have done a time series analysis where I could have predicted future trends for the Boulder housing market. Nonetheless, it seems as though it would be a great idea for all of us to invest into the real estate market in Boulder County because it could have a huge payout in the future. However, if you do plan on doing that, make sure that you are ready to invest a pretty penny!