Is there a relationship between demographic and real estate market data?

2 min read

The growth of a specific area is one of the biggest concerns that real estate investors have regarding their current and future investments.  But what types of data should we look up and how these data are related to each other? I have researched the data that are often used to make suggestions for the best areas to invest in real estate and analyzed whether there is a statistical relationship between them.

The data points you might often see on blogs about “hot areas to invest in real estate” can be divided into two categories; demographic and market data. The demographic data shows insights into people’s lives in the area while the market data simply tells you the housing market trend. The suggestion for areas to invest in real estate are the outcome of the research on both the demographic and market data. The data points that are often used to find good places to invest are the followings;

  • Demographic
    • Population Growth
    • Unemployment Rate Change
  • Real Estate Market
    • Rent Change Year Over Year
    • Sales Price Change Year Over Year

Let’s take a look at these data by states and what are the top and bottom cities in each topic.

Population Growth

Source: Census Bureau

Population growth represents how fast new people are coming to the cities, which can increase the demand for housing. According to Census’s National Population Totals and Components of Change, the top 5 states with population growth are;

  1. Idaho (2.09%)
  2. Nevada (1.75%)
  3. Arizona (1.69%)
  4. Utah (1.66%)
  5. Texas(1.28%)

And the bottom 5 states are;

  1. West Virginia(-0.67%)
  2. Alaska (-0.49%)
  3. Illinois (-0.4%)
  4. New York (-0.39%)
  5. Hawaii (-0.33%)

Unemployment Rate Change

Source: U.S. Bureau of Labor Statistics

The more unemployment rate declines, the healthier the city’s economy will be and people can maintain their lives with paying checks. According to the U.S. Bureau of Labor Statistics, the 5 cities that decreased unemployment the most in the country are;

  1. South Carolina (-1.00%)
  2. Alabama (-0.90%)
  3. Illinois (-0.90%)
  4. Oregon (-0.90%)
  5. Colorado (-0.70%)

On the other hand, the cities that increased the rate the most are;

  1. Louisiana (0.60%) 
  2. Pennsylvania (0.60%)
  3. Delaware (0.50%)
  4. Mississippi (0.40%)
  5. Wisconsin (0.40%)

Rent Amount 

Source: Apartment List

Rent amount change over a year represents how the rental market has changed. The rent growth is an important indicator of the competitiveness of rental properties in the area. Apartment List calculates the growth rate based on the median rent statistics from the Census Bureau American Community Survey. The top 5 cities with increasing rent amount are;

  1. Delaware (3.90%)
  2. Arizona (3.60%)
  3. Alabama (2.90%)
  4. Nevada (2.60%)
  5. North Carolina (2.50%)

The 5 cities with the least rent amount increase are;

  1. Louisiana (-0.80%)
  2. Alaska (0.50%)
  3. South Dakota (0.50%)
  4. Kentucky (0.60%)
  5. Vermont (0.60%)

Sales Price

Source: Zillow

For real estate investors, the change of listed sales price of properties over a year gives critical insights into investment properties in the area. Zillow shared the statistics about the real estate market from their services including listed house sales price. The top 5cities with the largest increase in median listed price are;

  1. Idaho (8.00%)
  2. Alabama (7.30%)
  3. New York (7.30%)
  4. Massachusetts (6.90%)
  5. New Jersey (6.60%)

On the other hand, the 5 cities with the least increase are;

  1. Nebraska (-7.00%)
  2. North Dakota (-4.40%)
  3. Vermont (-2.20%)
  4. Hawaii (-1.60%)
  5. Texas (-0.20%)

So is there any statistical relationship between demographic and real estate market data?

When I analyzed the variance of population growth with rent change and sales price, I could see some influence from population growth to rent price. The R-Squared from population growth to rent change was 0.3, which means population growth might increase the rent price. On the other hand, the R-Squared from population growth to listed sales price was 0, which means there is no influence from the population growth on the list price.

While at least I could see some relationship between population growth and rent price, I could not find the statistical relationship for the unemployment rate change on both rent price and sales price. The R-Squared from unemployment rate change to rent change and list price were less than 0.1, which means there is no relationship between these numbers.

Conclusion

After searching the data that are often used as indicators of the growth of cities, I found out there was no significant statistical relationship between each data I collected. This shows that while the demographic data and market data are used to understand the perspectives of the real estate market in local areas, it is hard to say these data are strongly related to each other as a broader spectrum. 

This result can give a possibility that the real estate market data like rent amount and sales price are influenced by many more variables than just population and job number. I believe real estate business is much more localized than data at the state level can show. The statistical study should be done at the city level rather than the state. That means stay tuned! I will continue some research further. 

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