Data centers can affect nearby housing in three different ways, and the evidence is not equally strong for each. A 2026 transaction study found that large facilities were associated with an average 3% home-value decline within three miles over the following five years and a 7.2% decline within one mile. Other regional research found no additional discount after accounting for all industrial properties. Data centers can greatly expand a jurisdiction’s tax base, but that does not automatically raise an individual homeowner’s bill. No authoritative source establishes a standard homeowners-insurance surcharge based solely on distance from a data center.
For a purchase decision, the useful unit is the specific parcel: its distance from the facility, the project’s size and power capacity, announcement and construction dates, surrounding land uses, local tax rules, and an address-specific insurance quote.
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What the strongest home-value evidence shows
A national transaction study found a localized decline
Garrison Schlauch and Simon Greenhill’s 2026 matched stacked event study examined housing transactions around announcements of large data centers. It estimated an average 3% reduction in home values within three miles during the five years after an announcement, with an average 7.2% reduction within one mile. The study reports that the effect persisted for at least five years rather than disappearing immediately after construction began.
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A regional study reached a different conclusion
Fairfax County’s 2026 summary of a 2023 George Mason University Center for Regional Analysis study says the analysis found “no marginal negative effect of being closer to a data center” after accounting for all industrial properties. Fairfax also says the county has not conducted its own analysis of home values. This result does not disprove the national study; it indicates that the estimated effect can change when data centers are compared with other industrial land uses and when local market conditions differ.
Survey and county comparisons show correlation, not causation
The National Association of REALTORS’ 2026 Data Center Impact Report surveyed REALTORS and found that 25% saw a positive nearby residential effect while 22% saw a negative effect. The same report found a $431,750 median home value in counties with at least 10 data centers, compared with $174,500 in counties without data centers. NAR cautions that counties with many facilities were already higher-income technology hubs, so the comparison cannot show that data centers caused the higher values.
NAR Chief Economist Lawrence Yun summarized the limitation this way: “There is no single data center effect. Instead, the story varies significantly depending on the local market.” A countywide median therefore cannot substitute for comparable sales around the facility you are evaluating.
How distance, timing, and design change the result
Distance is a useful first screen, not a complete valuation model. The available evidence supports the following framework:
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| Location relative to a large facility | What the 2026 transaction study estimated | Questions that can change the local result |
|---|---|---|
| Within 1 mile | 7.2% average decline over the five years after announcement | Is the building visible or audible? Is there a buffer, highway, rail line, or other industrial use between the home and the site? Is this the area’s first large facility? |
| 1–3 miles | Part of the study’s 3% average decline within three miles | How large is the campus, and where are substations, cooling equipment, access roads, and construction traffic located? |
| Beyond 3 miles | Smaller effects were reported, but the 2026 transaction study does not provide a separate percentage | Do local amenities, employment, utility projects, or broader land-use changes outweigh any nuisance effect? |
The clock matters as well. A public announcement can change buyer expectations before construction. During construction, truck traffic, dust, road closures, and uncertainty may be more prominent. Once operating, the relevant issues may shift to mechanical noise, lighting, security, backup generators, water infrastructure, and the visual scale of the campus. A home purchased before an announcement and one purchased after operations begin are not exposed to the same information set.
Facility characteristics matter because a hyperscale campus with high electrical capacity can have a different footprint, substation requirement, and traffic pattern from a smaller enterprise facility. Existing industrial zoning and intervening uses can also reduce the incremental effect of one more project. Conversely, a large project in a previously residential or rural setting may create a sharper change in what buyers see and hear.
What data centers do to property taxes
Why the tax base can grow quickly
A data center contributes taxable land, buildings, and often a large amount of business personal property such as servers, power equipment, and cooling systems. Because that equipment can be worth more than ordinary commercial contents, a small number of facilities can represent a substantial share of a county’s commercial assessment.
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Published local revenue examples
| Jurisdiction and source year | Published figure | How to interpret it |
|---|---|---|
| Fairfax County, FY2027 | $110.6 million in data-center revenue; approximately $260 for the average homeowner’s FY2027 real-estate-tax bill | Fairfax says most revenue comes from business personal-property taxes on equipment, which depreciates under the county’s schedule. The $260 is an average bill equivalent, not a charge assigned to every home near a facility. |
| King and Pierce counties, Washington JLARC review, 2022–2025 | Taxable value rose from $239.2 million to $350.2 million; total taxes paid rose from $2.4 million to $3.55 million | JLARC says it is unclear how much growth came from a data-center tax preference versus routine equipment replacement or other investment. |
| Prince William County, tax year 2023 | Data centers accounted for 42% of commercial assessments | This describes the commercial tax base, not the assessed value of nearby residential parcels. |
Why more commercial revenue may not raise your bill
Your residential tax bill depends on the assessed value of your parcel, the jurisdiction’s tax rate, special-district levies, exemptions, the reassessment calendar, and any equalization process. A county can receive substantial data-center revenue and use it to fund schools, roads, public safety, or tax-rate reductions without changing the assessed value of a neighboring house.
Conversely, if new infrastructure or service costs require higher levies, a homeowner could see a larger bill even if the home’s market value is unchanged. Public services may also affect future home prices, but that capitalization is a local market question rather than an automatic tax rule.
Before relying on a tax estimate, ask the assessor or treasurer:
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- When is the next residential reassessment, and what equalization or phase-in rules apply?
- Which county, municipal, school, utility, and special-district levies appear on the bill?
- Are exemptions, homestead caps, or assessment limits available for this parcel?
- How is data-center revenue allocated, and are there planned capital or emergency-response costs?
Does living near a data center raise homeowners-insurance premiums?
No published proximity surcharge has been established
The National Association of Insurance Commissioners’ 2018–2024 market analysis describes insurance conditions as local and driven by weather risk, rebuilding costs, claims patterns, and insurer participation; it does not list data-center distance as a standard national rating factor.
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The Government Accountability Office says insurers generally begin with a base rate and adjust for property and geographic risk, including construction, replacement cost, catastrophe exposure, crime, and distance to fire stations or hydrants. Its 2026 review found that the average U.S. homeowners premium increased 3% after inflation from 2019 to 2024. Homes in severe or extreme wind-risk areas had premiums about 58% higher than comparable homes in major-risk areas. Those figures describe broad insurance conditions, not a data-center effect.
What could matter at a particular site
An insurer may consider a facility-related circumstance if it changes an established risk factor. Examples include a new access route that affects emergency response, utility or substation infrastructure, wildfire exposure, flood drainage, construction quality, or a documented local claims pattern. Mechanical noise or lighting may affect livability and resale without being a separately priced insurance hazard. There is no evidence here for applying a percentage surcharge based on a home’s distance from a campus.
Maine Bureau of Insurance guidance lists replacement cost, construction type, distance to the fire department, coastal exposure, home age, heating method, and claim history among rating factors. Those examples illustrate why two homes equally close to a facility can receive different premiums.
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How to obtain a useful quote
- Give the insurer the exact street address, not merely a ZIP code or a distance estimate.
- Ask whether the underwriter considers any facility-specific hazard, emergency-response route, utility infrastructure, noise-related claim history, wildfire, flood, wind, or fire-protection issue.
- Request the same coverage limits, deductible, replacement-cost basis, and endorsements from multiple insurers so the quotes are comparable.
- Ask whether the quote is contingent on an inspection, updated roof information, flood coverage, or a separate equipment or service-line endorsement.
- Recheck availability and price after construction if the facility is not yet operating; insurers can change underwriting appetite even when no formal proximity factor exists.
A parcel-level due-diligence process for buyers
1. Map the actual exposure
Measure the distance from the home’s parcel boundary and primary living areas to the data-center buildings, substations, generator yards, cooling equipment, and truck entrances. “One mile from the campus” can conceal a much shorter distance to a particular noise or traffic source. Identify intervening industrial parcels, roads, rail lines, terrain, and planned expansions.
2. Build a dated project timeline
Record the first public announcement, zoning or permit filings, construction start, expected energization, and operating date. Pull planning-board minutes, environmental documents, traffic studies, and utility filings. A home bought before an announcement carries a different information risk from one bought after the operating conditions are observable.
3. Test the value claim with comparable sales
Ask a local appraiser or agent for sales matched on size, age, condition, school assignment, lot, and neighborhood, separated by distance and by announcement or operating period. Look for repeated sales or a broad set of transactions rather than one high or low listing. The 3% and 7.2% estimates are useful benchmarks for questions, not an adjustment to paste into an appraisal.
4. Verify the tax mechanics
Obtain the parcel’s current assessment and tax bill, then identify the next reassessment date, tax-rate proposals, special districts, exemptions, and any announced infrastructure levies. Ask whether the jurisdiction assesses data-center equipment as business personal property and how depreciation affects collections. Separate a change in the home’s assessed value from a change in the tax rate.
5. Get insurance quotes before waiving contingencies
Provide the exact address and construction details to several insurers. Compare deductibles, replacement-cost treatment, exclusions, service-line coverage, flood or wind endorsements, and cancellation or nonrenewal terms. Treat an insurer’s inability to offer coverage as a separate market signal from the quoted premium.
6. Visit under different conditions
Inspect the property during weekday construction or operating hours, at night, and during weather that reveals drainage, generator noise, lighting, or traffic. Speak with nearby residents, but verify anecdotes against permits, code complaints, and measurable property data.
Decision guide: when proximity deserves the most caution
- Highest uncertainty: a first large or hyperscale facility within one mile, before construction impacts and operating noise are known.
- Moderate uncertainty: a project one to three miles away where traffic, substations, or expansion phases are still unresolved.
- Potentially lower incremental effect: a facility in an established industrial or data-center cluster with buffers and observable operating conditions, although the parcel still needs its own sales and insurance analysis.
- Tax concern: a jurisdiction relying heavily on business personal-property revenue or proposing new service levies; review the budget rather than assuming commercial growth lowers household taxes.
- Insurance concern: a site that changes an existing catastrophe, fire-response, flood, wind, or utility risk. Distance by itself is not a demonstrated rating factor.
What a buyer should conclude
Recent causal evidence supports a localized home-value risk near large data centers, especially within one mile, but regional research and professional surveys show that the direction and size of the effect vary. The fiscal effect is clearer at the jurisdiction level: facilities can add significant taxable property, while the household result depends on assessment rules, levies, exemptions, and how revenue is spent. For insurance, obtain address-specific quotes and investigate ordinary hazards; do not assume a data-center surcharge that insurers and regulators have not documented.
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