SP1000 Companies’ Impact on Housing Prices

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SP1000 Companies Impact on Housing Prices

Where companies are, jobs are. Where jobs are, is where people live. I’ve been very interested in breaking down the true correlation between companies and the sub sequential on housing prices.

Jane Jacobs’ theorizes in the “City and the Wealth of Nations” that a prosperous “import-replacing” city contains a thriving amalgamation of positive economic production and activity. This means that where economics units, or companies work, people will follow, and thus housing will be in demand.

While home prices are determined in finality between the equilibrium of supply (IE: how many houses are in the market) and the demand (who actually wants to buy the homes), a rough assumption can be made that the more companies in a set area, the more people will want to live, and the higher home prices will be.

As a rough analysis, I look at the top 1000 SP companies in the US and correlate
(1) The number of companies head-quartered in each state, by
(2) The average 2014 housing price in the state.

While a “city” is more precise, I chose state because the many people will live in a well-off neighborhood, but commute several miles over somewhere else to work. For example, there are few (or zero) Fortune 1000 companies headquartered in Atherton, but most people drive down 5-15 minutes to work at Google or well known venture capital companies. Atherton’s average home price was close over $5M several years ago.

A simple linear regression shows that each additional SP1000 company headquartered in a state responds to an average of $835 additional dollars.

Average Housing Price in a State = $835.62(Number of Companies in State) + $233,496.

The tiny incremental upside of $835 per incremental headquartered company can mean either that employment doesn’t actually increase housing prices, or that this analysis is far too noisy. My vote is on the latter. I believe this level of analysis is simply too rough and does not capture enough features. For example, if you look at the graph, you can see one strange outlier with 2 companies but a huge state sales prices of almost $600K. That is Hawaii, and we can easily imagine the customer demand even though the state lacks many SP1000 companies.

There are many other factors that contribute to this noise. A companies headquarters does not mean that everyone will work there. For example, many retailers have massive employment ramifications across many different states. Further, there are many companies not captured in my list of SP1000. A more comprehensive analysis would involve looking at the offices that are actually hiring people, factor in the salaries, allow workers to commute between nearby locations, and factor in each regions zoning. Additionally, certain zoning laws and other housing supply restrictions may artificially result in higher prices beyond the number of people demanding homes. It will be fascinating to dive deeper and better track economic activity to see the true impact on housing price sales.