Sunday, September 15, 2024

Home Prices across USA and other metrics

In this blog post, I delve into an extensive collection of data and computations related to home prices across the United States. I examine the affordability of homes in each state, including Washington D.C., by taking into account regional income, down payment, loan costs, and mortgage payments. I also consider the minimum salary requirements needed to maintain home ownership. From this, I derive metrics such as the affordability gap, affordability index, and the ratio of home price to income. In addition, I’ve gathered data on other influential factors like quality of life, crime rate, and unemployment rate. By interpolating these various data points, I aim to uncover relationships and trends such as, how do cost of living, affordability of a home, and crime rate relate to each other, taking a deeper look at the top 5 most affordable places vs top 5 least affordable places, and much more. This is a comprehensive collection of data and insights.

Methodology: The fundamental data is drawn from GoBankingRates for each location’s (state + DC) Median Home Prices. Then from Bing, I was able to get each location’s median household income. With that information, I was then able to able to then derive the downpayment, loan amount, monthly mortage payments, and the minimum salary requirements, using the following assumptions applied across all states: a 30-year fixed rate mortgage with 20% down payment with a rate of 6.82% as sourced from Freddie Mac, and there was no P&I, HOA fees, or property tax included, housing costs could not exceed 30% of gross income. This part of the data is up to date as of April 10, 2024. From there, I was able to calculate metrics on Affordability. For example, Affordability Gap % = (SalaryReq – Median Household Income / SalaryReq) * 100 or, =(([@SalaryReq]-[@[Median Household Income]])/[@SalaryReq])*100

So, the more affordable, smaller the number (even negative if median income is higher than the min salary requirement). Then I flip the Gap to Affordability Index by deducting the gap from 100. This gives us the percentage of people who can afford a home. Affordability Index = 100-[@AffordabilityGap] (Higher the value now, more people can afford a home). NOTE: Affordability index value ranges from 34 (least affordable) to 129 (most affordable) and has nothing to do with the number of states, therefore the scale does not from 1 to 50 for example.

Where SalaryReq is the minimum income needed to comfortably afford a home purchase. If the downpayment is 20% of the home price, we can easily find the outstanding loan amount. Then I applied the following formulas that perfectly fitted various other data sources:

Monthly Mortage = Loan Amount / 153.079
Min Salary Required = Loan Amount / 3.83

Price:Income column is the ratio of Home Price to Income for each state. For crime and quality of life data, I collected them from various sources such as: state-specific government sites, FBI data, CrimeGrade.org, etc. General categories of crimes: Violent Crimes (includes Assault, Robbery, Rape, Murder), Property Crimes (includes Theft, Vehicle Theft, Burglary, Arson), and Other Crimes (includes Kidnapping, Drug Crimes, Vandalism, Identity Theft, Animal Cruelty).

Unemployment data was sourced from U.S. Bureau of Labor Statistics. All numbers are rounded to nearest whole number.

I won’t share the entire dataset here as there are many and in many formats which I had to reshape into various tables for my analysis; instead, I’ll share some of the visuals/charts for easy digestion. The goal is here to share knowledge and provide some informative and interesting insights. I’ll share the overall picture, and then dig into details and cross-examine various factors with visuals based on all that data. All key formulas are explained in the methodology section here so I won’t repeat below for each visual.

Let’s start!

Home Affordability

About the chart: Home Affordability Gap %: The taller the bar, the less affordable (or, more Unaffordable). The bars that are below the X-axis (negative) indicate places where affordability is very high (more than 100% of the residents making at least median income can afford to buy a house there).
The numbers on top of bar shows what percent of population of the state cannot afford a house (e.g. 66% in Hawaii).
Takeaway: 3 most affordable: West Virginia, Iowa, Kansas. 3 least affordable: Hawaii, California, DC.

About the chart: Home Affordability Index: The taller the bar, the more affordable, the shorter the bar the less affordable. The numbers on top of bar shows what percent of population of the state can afford a house (e.g. 34% in Hawaii). The bars where values are above 100 indicate places where affordability is very high (more than 100% of the residents making at least median income can afford to buy a house there).
e.g. Arkansas, Pennsylvania and onward toward the right of the chart all the way to West Virginia.
Takeaway:

Less than half the population in these states/places can afford a house there: Hawaii, California, District of Columbia. Only about half the population can afford a house in Oregon, Washington, Montana, Idaho.Top 5 most expensive homes are on the west coast, exception being District of Columbia (aka Washington DC) which is on the east coast.

About the chart: The above chart is a different representation of the same data shown previously as clustered columns and is called a tree map. Darker colors and larger boxes indicate more people can afford to own homes. E.g. Only 34.4% of people in HI can afford to own a home whereas everyone earning at least a median income in PA can afford a home @ 100.9%

Factoring in Household Income

About the chart: The larger the gap between the green line and the top of the blue bars, the less affordabiity. The taller the blue bar, the more expensive the homes are for that state. The gray dashed horizontal line across is the average nationwide home prices. Any bar extending above that line is higher than average.

Takeaway:

There’s a large gap between home prices and median income in the area for all states show in chart that are left of VA (Virginia) making home purchases farther away from most residents’ reach with HI, CA, DC having the largest gap.

But maybe the incomes in those expensive places are enough to compensate for the gap? Let’s take a look at the incomes next.

About the chart: The gray dashed horizontal line across is the average nationwide income. Any bar extending above that line is higher than average. Here we get a quick look at which households by state earn more or less than the national average household incomes. These are in USD\$ not percentages.

Comparing Home Prices and Incomes with National Averages (Deltas in %)

So, the next thing to analyze may be to see how this looks if we consider the DIFFERENCE between incomes from national average and the DIFFERENCE between home prices from national average expressed in percentages change the picture. By doing the percentages instead of dollars, we can compare the house prices and incomes parity in one, uniform scale. Let’s do that.

About the chart: The above chart essentially tells us if the difference in income (from national average) make up for the difference in house price (from national average) for a state. Blue bars show the percent difference between home prices in the state and national average of home prices. The orange line shows the percent difference between household income in the state and national average of household incomes. They are both charted on the same scale.
If the blue bars are short or heading downward (negative), the home prices are that much % lower than national average home prices. The larger gaps between orange line and the blue bars indicate high disparity between home prices and income.

Takeaway:

WV has a very favorable home affordability as the prices are 137% lower than national average, and yet their income is just 31% lower than that of national average.

We notice that MD (Maryland) home prices are 12% higher than national average home prices, but their income is 27% more than national average income making it also favorable for home purchase.

HI (Hawaii) has home prices 62% above national average, but they earn only 21% more than national average incomes.

Understandably, there’s a lot of data in that chart. What if we break it down to two sets of charts each covering about 26 states/locations but adding another metrics: Disparity? I’ll call it Delta%. They would look like this:

About the charts: The two charts above also illustrate the difference in income (from national average) and if it’s enough to make up for the difference in house price (from national average) for a state. And since they show home price parity (delta%) from national average data sorted in descending order, we get a different angle to the same data.

– The blue bars indicate home prices relative to national average prices (if above the x-axis, prices are that much higher), and the orange bars show incomes relative to national average incomes (if above the x-axis, incomes are that much higher). Therefore, wherever the blue bar is taller than the orange bar for a state, it indicates less affordability. The green line is the difference between home price Delta (from national average) and income Delta (from national average) in percentage. The higher the green line, the less affordable (higher disparity) for those locals to buy a home in their state.

The visuals are split into two parts for readability, as there’s a lot of information packed into each. The first chart above covers HI (Hawaii) to MN (Minnesota) and the second one covers NC (North Carolina) to WV (West Virginia).

Takeaway:

First chart: In AK (Arkansas) the house prices are 2% lower than national average, but their income is 25% higher than that of national average.
In CA (California), the house prices are 53% higher than national average, but their income is only 12% higher than that of national average.

HI (Hawaii), CA (California), DC (District of Columbia), OR (Oregon), MT (Montana), ID (Idaho), WA (Washington), AZ (Arizona), FL (Florida) have some of the highest disparities between income and home prices there.

Conversely, AK (Arkansas), MD (Maryland), CT (Connecticut), VA (Virginia), DE (Delaware), WY (Wyoming), MN (Minnesota) have favorable disparity meaning their median incomes are far more than the minimum required for home ownership. Such disparity is made clearer visually by the green line. The higher it is above the x-axis, the harder it is to buy a home…if the green line is below x-axis, it mean residents of that state have income more than they need to afford to buy a home.

Second chart: Clearly we see WV (West Virginia) has 137% lower prices on houses albeit their median income is 31% lower than national average making the disparity very low (green line).
Virtually, all of these states have much more home affordability than in the first set of states in the previous chart.

Adding Price:Income Ratio into the Picture

About the chart: The gray dashed horizontal line across is the average Price:Income Ratio across USA. Any bar extending above that line has higher than average ratio. Taller the bar, the bigger the disparity between home prices and household income.

Takeaway:This picture clearly supports our previous findings regarding affordability metrics.

Adding More Factors: Crime | Quality of Life | Unemployment Rate | Cost of Living

I don’t have any standard or consistent quantitative data on quality of life factor, but by understanding some key qualitative data when considered along with some concrete numbers may help us get additional insights. For the sake of conciseness, I will only focus on top 5 of MOST affordable states and top 5 LEAST affordable states.

So far we have found these top 5 LEAST affordable states when it comes to buying a home:

⬇️ Hawaii (HI), California (CA), District of Columbia (DC), Washington (WA), Oregon (OR).

And these are the top 5 MOST affordable states when it comes to buying a home:

⬆️ Mississippi (MS), Oklahoma (OK), Kansas (KS), Iowa (IA), West Virginia (WV)
Here are their general key attributes that came up with respect to quality of life factors:

Crime & Affordability (Top & Bottom 5 Affordable)

Takeaway:
We see Mississippi, West Virgina, Iowa have relatively low crime rate and being highly affordable.
Hawaii, California have highest crime rates in this collection and yet have the lowest affordability.
Kansas has one of the highest crime rates but is highly affordable.
This shows us that crime does not always lower the home prices directly, other factors such as employment, climate, scenery, infrastructures play a major role in population growth
and ultimately, in home prices.

Unemployment & Affordability (Top & Bottom 5 Affordable)

Takeaway:
Kansas, Iowa, Hawaii have relatively low unemployment rates (2.7 to 3.1%) of which Kansas and Iowa remain very affordable. However, we saw in previous chart that Kansas has very high crime rate.

Cost of Living Grade & Affordability (Top & Bottom 5 Affordable)

– The left y-axis is for Cost of Living Grade; right y-axis is for Affordability Index. CostGrade is based on cost of living data from 50 states + DC.
– Lower CostGrade value means higher cost of living. Higher value means lower cost of living.
– Higher AffordabilityIndex value means homes are affordable to more residents of the state; and vice versa.

Takeaway:
Here we see a direct relationship and clearer correlation between Affordability and cost of living (transformed here as CostGrade), meaning the lower the affordability, lower the rank value (CostGrade for HI is 1 meaning it’s the most expensive to live there).
The house prices affect the overall cost of living (rent or ownership) thereby lowering the overall affordability at high cost of living conditions.
We see Kansas, Mississippi, Oklahoma have some of the lowest cost of living while they highly affordable places to own a home.

Cost of Living Grade & Affordability & Crime Rate Relationsips (Top & Bottom 5 Affordable)

– The left y-axis is for Crime/100K; right y-axis is for Affordability Index and CostGrade.
– CostGrade is based on cost of living data from 50 states + DC.
– Lower CostGrade value means higher cost of living. Higher value means lower cost of living.
– Higher AffordabilityIndex value means homes are affordable to more residents of the state; and vice versa.

Takeaway:
Here we see the clearer correlation between Home Affordability and cost of living (transformed here as CostGrade)…they seem to follow very similar trends and in the same direction.
Remember, higher the Affordability Index, the home prices are more within reach (good), and higher the Cost Grade, the cheaper is to live overall in that state (good).
When CostGrade is higher for a state (meaning, good grades, meaning lower cost of living), generally the home affordability will also be higher; and vice versa.

➜ The crimes in Kansas, Hawaii, and Californing are among the highest but Kansas gets high marks on CostGrade and Home purchase affordability while Hawaii and Californing despite the crime rate, rate much worse on home affordability and overall cost of living.
Mississippi, West Virginia, Iowa have all relatively low crimes with high home purchase affordability and overall lower cost of living.

In conclusion, the dynamics of home affordability across the USA are influenced by a myriad of factors, from economic indicators to regional trends. In this post we explored some important metrics to provide valuable insights across the nation and at a little deeper level for selected regions. It’ll be surely interesting to see how this landscape and ranking change over time. I also hope the visuals have been educational and helpful.

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