U.S. Property Taxes Levied on Single Family Homes in 2019 Increased to More Than $306 Billion

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Average Property Tax Was $3,561, Up 2 Percent with an Effective Tax Rate of 1.14 Percent; Highest Effective Tax Rates in Illinois, New Jersey, Texas, Vermont, Connecticut

IRVINE, Calif. – April 9, 2020 — ATTOM Data Solutions, curator of the nation’s premier property database and first property data provider of Data-as-a-Service (DaaS), today released its 2019 property tax analysis for more than 86 million U.S. single family homes, which shows that property taxes levied on single family homes in 2019 totaled $306.4 billion, up 1 percent from $304.6 billion in 2018 and an average tax amount of $3,561 per home — an effective tax rate of 1.14 percent.

The average property taxes of $3,561 for a single-family home in 2019 was up 2 percent from the average property tax of $3,498 in 2018, and the effective property tax rate of 1.14 percent in 2019 was down from the effective property tax rate of 1.16 percent in 2018.

The report analyzed property tax data collected from county tax assessor offices nationwide at the state, metro and county levels along with estimated market values of single-family homes calculated using an automated valuation model (AVM). The effective tax rate was the average annual property tax expressed as a percentage of the average estimated market value of homes in each geographic area.

“Property taxes levied on homeowners rose again in 2019 across most of the country. But the nationwide increase was the smallest in the last three years, a sign that cities, towns and counties are taking stronger steps to clamp down on how much they hit up property owners to support schools and local government services.” said Todd Teta, chief product officer for ATTOM Data Solutions. “Without major changes in the way local government and educational systems are funded, demands for good schools and other services will continue to put upward pressure on property taxes. But on balance, 2019 was a relatively mild year for taxpayers around the nation.”

Illinois, New Jersey, Texas, Vermont, Connecticut post highest property tax rates

States with the highest effective property tax rates were Illinois (2.22 percent), New Jersey (2.19 percent), Texas (2.11 percent), Vermont (2.11 percent), and Connecticut (2.04 percent).

Other states in the top 10 for highest effective property tax rates were New Hampshire (1.93 percent), New York (1.87 percent), Pennsylvania (1.75 percent), Ohio (1.68 percent), and Nebraska (1.57 percent).

Among 220 metropolitan statistical areas analyzed in the report with a population of at least 200,000, those with the highest effective property tax rates were Binghamton, New York (3.11 percent); Syracuse, New York (3.00 percent); Rockford, Illinois (2.84 percent); Rochester, New York (2.80 percent); and Atlantic City, New Jersey (2.60 percent).

Property taxes increase faster than national average in 56 percent of markets

Out of the 220 metropolitan statistical areas analyzed in the report, 123 (56 percent) posted an increase in average property taxes above the national average of 2 percent, including Atlanta, Georgia (9 percent increase), Phoenix, Arizona (9 percent increase); Miami, Florida (5 percent increase); Washington, DC (4 percent increase); and Boston, Massachusetts (4 percent increase).

Other major markets posting an increase in average property taxes that was above the national average were Detroit, Michigan (up 9 percent); Austin, Texas (up 9 percent); Denver, Colorado (up 8 percent); Las Vegas, Nevada (up 7 percent); and Charlotte, North Carolina (up 5 percent).

Hawaii, Alabama, Colorado, Utah, Nevada post lowest property tax rates

States with the lowest effective property tax rates were Hawaii (0.36 percent), Alabama (0.48 percent), Colorado (0.52 percent), Utah (0.56 percent), and Nevada (0.58 percent).

Other states in the top 10 for lowest effective property tax rates were Tennessee (0.61 percent); West Virginia (0.61 percent), Delaware (0.62 percent), Arizona (0.63 percent), and Wyoming (0.65 percent).

Among the 220 metro areas analyzed for the report, those with the lowest effective property tax rates were Daphne, Alabama (0.33 percent); Honolulu, Hawaii (0.35 percent); Montgomery, Alabama (0.38 percent); Tuscaloosa, Alabama (0.39 percent); and Colorado Springs, Colorado (0.41 percent).

11 counties with average annual property taxes of more than $10,000

Among 1,448 U.S. counties with at least 10,000 single family homes, those with the highest average property taxes on single-family homes were largely located in the greater New York metro area, led by Westchester County, New York ($18,103); Rockland County, New York ($13,048); Marin County, California ($12,250); Essex County, New Jersey ($12,206); and Nassau County, New Jersey ($11,952).

About ATTOM Data Solutions

ATTOM Data Solutions provides premium property data to power products that improve transparency, innovation, efficiency and disruption in a data-driven economy. ATTOM multi-sources property tax, deed, mortgage, foreclosure, environmental risk, natural hazard, and neighborhood data for more than 155 million U.S. residential and commercial properties covering 99 percent of the nation’s population. A rigorous data management process involving more than 20 steps validates, standardizes and enhances the data collected by ATTOM, assigning each property record with a persistent, unique ID — the ATTOM ID. The 9TB ATTOM Data Warehouse fuels innovation in many industries including mortgage, real estate, insurance, marketing, government and more through flexible data delivery solutions that include bulk file licenses, property data APIs, real estate market trends, marketing lists, match & append and introducing the first property data delivery solution, a cloud-based data platform that streamlines data management – Data-as-a-Service (DaaS).

Media Contact:

Christine Stricker

949.748.8428

christine.stricker@attomdata.com

Data and Report Licensing:

949.502.8313

datareports@attomdata.com

Please contact us if you have questions about the underlying data referenced in this article, or would like to have access to that data in the form of custom reports, API, Bulk File or DaaS.

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