Income and Home Ownership
Here is a story in three graphs about home ownership and income in the US (and in particular in California and Texas).
This exercise is intended to 1) get users more familiar with the SIPP data set, 2) provide a first example of how that this data can be used to answer interesting questions, and 3) serve as a springboard to more and more interesting insights.
We analyzed 2023 data from the SIPP data set of ~100k families.
Income Distribution
As we all know, the average income in California is higher than the average income across the US (as well as in Texas). In our dataset, average monthly household income in CA was mean = $12,400, median = $8400. In Texas it was mean = $9600, median = $6000. And across the US it was mean = $10,500, median = $7000.
Below is the distribution, and you can clearly see that California over-indexes on higher incomes and under-indexes on lower incomes, and Texas is the reverse
Home ownership status by income
Not surprisingly, across all three of these regions, the higher a family’s income, the more likely it is to own its home. In general the percentage is below 50% for very low income families, and then above 80% for the highest income families.
Given the well-known higher cost of California real estate, it is not surprising that the percentage of homeowners in California in each bracket is on average about 15% below the national average, while Texas is slightly above (particularly at both ends of the spectrum).
Given the higher average income in California, we wanted to renormalize this chart for income percentile (i.e. compare the 50th percentile home according to income across each region, the 25% and so on.
The results are in the chart below. We fit a polynomial to the data. All in all though the chart tells pretty much the same story. Any way you look at it, home ownership in California is less likely.
What next?
A few next questions:
- How do wealth levels interact here?
- What is the relative wealth in each region and what does home ownership look like at different wealth levels
- How do incomes drive wealth in each region?
- What is relevant wealth growth of different regions?
- What is sustainable income level of different regions?
- With and without housing
- Who is moving?
- Our data set on families that move is relatively small, but adding a few more years we can start to look at
- What is relevant income level, wealth and home ownership of people that move
- How do they compare a year later?
- How has income changed? Especially in light of where they have moved from/to
- How has home ownership changed?
- Especially versus people who didn’t move
- How is wealth trending
- Especially versus people who didn’t move
- Our data set on families that move is relatively small, but adding a few more years we can start to look at
Why are we doing this?
It is important to remind ourselves of the ultimate goal so we can periodically re-evaluate and make sure we are looking at the right data and questions.
Some of our goals
- Help us understand
- Realistic wealth goals and attainability
- Tradeoffs
- For instance when one type of person moves how does that/ should that impact their future income, wealth, housing status (and ultimately other variables)
- We want to start making this forward looking
- Bring in trends of job growth and salaries
- By types of jobs and regions
- Bring in trends of job growth and salaries
