Poor air quality in the United States and its relationship with the housing industry, specifically home prices, remain relatively overlooked. The objective of this study is to measure the air quality of 50 US states and its subsequent effect on median home prices to understand whether air quality is a significant factor in measuring discrepancies in pricing.

Air quality and median home price data from the World Population Review were used in a regression to evaluate how air quality might affect the differences in home prices across the US. The analysis yielded the result that air quality is not a significant predictor of median home pricing (p>0.1). Instead, the variables that were most significant included certain race demographics, median annual income, bachelor’s degree attainment, and states in the West, Northeast, and South. The study concluded that air quality levels are not highly considered in the valuation of a home price, but with better transparency and access to local pollution information, we may see it become more significant. Furthermore, accurate demographic reporting and government aid toward marginalized communities with lower income levels is crucial to making housing more affordable. Increased financial aid for higher bachelor’s degree attainment is also necessary for all to be able to participate in the highly competitive and expensive housing market.

MedianHomePrice = 𝛼 + 𝛽1AirQuality + 𝛽2UrbanPop + 𝛽3Race + 𝛽4BachDegree +𝛽5Income + 𝛽6Poverty + 𝛽7GDPGrowth+ 𝛽8Region + 𝑢

In the model represented above, MedianHomePrice measures the median home price as it varies by state. AirQuality measures the level of air quality by state using the Air Quality Index (AQI, 0-500) which is found by calculating the four major air pollutants (ground-level ozone, particle pollution, carbon monoxide, and sulfur dioxide) as determined by the Clean Air Act. Lower values of AirQuality indicate cleaner air while higher values are more hazardous. UrbanPop represents the urban population as a percentage of the total population by state. Race represents the percentage of the total population by state that is racially Black, Hispanic, Asian, and Native; White population percentage is excluded. BachDegree measures the percentage of the total population by state that has received a Bachelor’s degree or higher. Income measures the median income by state. Poverty measures the poverty rate by state. GDPGrowth measures the GDP growth rate as it increases from quarter to quarter by state. Finally, Region controls our regression by geographic region; Midwest is excluded.

Contrary to this study’s hypothesis, the empirical results show that air quality is not a significant driver of state median home prices and contributes to the relatively ambiguous existing literature surrounding the relationship. Much like the more specific work done by Lu and Lee in South Korea that finds a decrease in local value property by 0.32% for every 1% increase in air pollution, our coefficient finds that for every unit increase in the air quality index (poorer air quality), we find that median home prices increase in response (Lu). However, contrary to their study, our finding is not significant. It is understood from the regression analysis that individuals might not consider air quality as a main factor when determining the worth of a house. We can also deduce that many prospective home buyers do not have easy access to local pollution and air quality information, and therefore it is not taken into account when deciphering the value of a home. If the government and other real estate entities bring this information to light in a digestible way and consider it more seriously, we may see an increased significance in air quality on the value of a home