Texas is a large state, massive actually.
Both by area and population, Texas is the second biggest state in the United States. It is home to six major cities: Houston, San Antonio, Dallas, Austin, Fort Worth, and El Paso. The Lone Star State carries 34 electoral votes, making it a key political theatre. Texas also boasts 54 Fortune 500 companies and consistently leads the nation in export revenue.
With Texas’ gigantic size comes a whole bunch of options to choose from. It may be a simple decision like choosing where you want to go for lunch or what park you want to go to.
Or, it could be a much more consequential decision like finding where you want to buy a home. Normally, this is a stressful process no matter where you live, but in Texas it becomes ten times as hard thanks to the state’s massiveness.
Luckily, LendEDU has licensed data that has helped us determine the 250 best towns in Texas to buy a home. Analyzing nearly 1,000 Texas towns, we shortened our list down to 250 places by using a unique equation that factored in three weighted parameters.
The three parameters were as follows:
- Home Income to Value Ratio Score (40%, listed in table as Value Score)
- Five Year Population Forecast Score (40%, listed in table as Population Score)
- Five Year Income Forecast Score (20%, listed in table as Income Score)
The Home Value to Income Ratio Score represented the ratio between a town’s median household income and the same town’s median home value. The Five Year Population Forecast Score indicated the predicted growth of a town’s population over the next five years. The Five Year Income Forecast Score was based on the predicted growth of a town’s median income over the next five years.
Together, these indicators helped develop a score that could accurately assess which towns in Texas would give potential homebuyers the most return on their real estate investment.
The towns featured below are the 250 best towns in Texas to buy a home in 2017.
Ranking the Best Places to Buy a Home in Texas
All figures, aside from location data, presented in this publication were derived through calculations using data provided by Onboard Informatics as licensed by LendEDU. The data used in our calculations included the median home value, the median household income, the median five-year household income projection, the current population, and the five-year population projection. All data was originally broken out by zip code, but the data set was simplified down to town and city names. Data for cities and towns with multiple zip codes were averaged together and weighted by population. After the initial weighting procedure, we were dealing with over 1,000 Texas towns and cities, but that number was cut down with an arbitrary population cutoff of 3,500.
We determined the home income to value ratio by simply dividing median household income by median household value. The value ratios were ranked against each other on a percent scale of 0 to 100 percent. Each individual percent rank was multiplied by its weight to produce the value score. The maximum possible value score was forty points. This score was meant to represent the value a town’s residents could expect from a typical home purchase in a respective town.
The second parameter, Five Year Population Forecast Score, was determined using the current population and five-year projected population figures. A percent change equation was used to figure out the percent increase or decrease in population over five years. Each individual percent change was ranked on a percent scale against the field. The percent scaled ranged from 0 to 100 percent. Each percent rank was multiplied by its weight to produce its Five Year Population Forecast Score. The maximum value for this score was forty points.
The third parameter, Five Year Income Forecast Score, was determined using the median household income and the five-year median household income projection. A percent change equation was used to determine the percent increase or decrease in income over the next five years for each city and town. The values were ranked against each other using a percent rank function in excel; the percent scale was from 0 to 100 percent. Each individual percent rank was multiplied by its weight to produce the Five Year Income Forecast Score. The maximum value for this score was twenty points.
After all scores were determined, they were summed up for a final score for each town. A score closer to 100 was considered favorable. The top 250 cities and towns by final score were included in the report.
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