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Short answer: A data center can reduce nearby home values, increase local government revenue, or have little measurable effect, depending on its size, distance, timing, setting, and the local tax and insurance systems. Recent causal research found the clearest price discounts very close to large facilities, while other studies found no additional effect after accounting for industrial land uses. Data-center proximity by itself is not an established homeowners-insurance rating factor.
For a purchase decision, treat the specific parcel—not a county average—as the unit of analysis. Compare sales at several distances, review assessment and tax-district records, and obtain insurance quotes for the exact address before making an offer.
What the strongest evidence says about home values
A national event study found a localized decline
A 2026 matched stacked event study by Garrison Schlauch and Simon Greenhill examined housing transactions around announcements of large data centers. It estimated an average 3% reduction in home values within three miles over the following five years, with an average 7.2% reduction within one mile. Effects were smaller farther away and persisted for at least five years in the study period.
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The study did not treat every facility as interchangeable. Discounts were larger for hyperscale or otherwise high-capacity projects, in urban locations, and when the project was the first large data center in an area. An announcement can therefore matter before construction is complete: buyers may price in expected traffic, utility infrastructure, noise, views, or future expansion.
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A regional study reached a different conclusion
Fairfax County’s summary of George Mason University’s 2023 Center for Regional Analysis study says that, after accounting for all industrial properties, there was “no marginal negative effect of being closer to a data center.” Fairfax also says the county has not conducted its own analysis of home values. This result may reflect a market where data centers are one part of a broader industrial landscape, rather than a clean comparison between otherwise identical neighborhoods.
Professional surveys show a split outcome
The National Association of REALTORS’ 2026 Data Center Impact Report is descriptive rather than a causal test. Among surveyed REALTORS, 25% reported a positive nearby residential effect and 22% reported a negative effect. Counties with at least 10 data centers had a median home value of $431,750, compared with $174,500 in counties without data centers. NAR cautions that the former counties were already higher-income technology hubs, so the comparison cannot show that data centers caused the difference. NAR Chief Economist Lawrence Yun summarized the evidence this way: “There is no single data center effect. Instead, the story varies significantly depending on the local market.”
These findings are not mutually exclusive. A high-capacity facility beside an established neighborhood can create a localized discount, while a technology-oriented county may gain jobs, services, and tax-funded amenities that support prices elsewhere. A county-wide median cannot substitute for comparable sales around the facility you are evaluating.
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How distance, timing, and design change the result
| Factor | What to examine | Why it can matter |
|---|---|---|
| Within 1 mile | Direct sightlines, cooling equipment, substations, construction access, and road changes | The 2026 event study found its largest average price effect in this band. |
| 1–3 miles | Traffic routes, transmission corridors, nighttime lighting, and cumulative development | The same study found a smaller but still measurable average effect across this wider band. |
| Beyond 3 miles | Regional labor, tax, utility, and housing-supply effects | Local benefits or costs may remain, but the study reported smaller proximity discounts. |
| Public announcement | Rezoning, permits, utility reservations, and announced capacity | Expectations can change comparable sales before operation. |
| Construction | Heavy vehicles, dust, road closures, work hours, and temporary noise | Construction impacts may be severe but temporary; check schedules and mitigation agreements. |
| Operation | Mechanical noise, lighting, security, backup generation, and water or power infrastructure | Operating conditions determine the long-term experience of nearby residents. |
| Hyperscale or high-capacity facility | Building footprint, electrical load, cooling system, and expansion phases | Larger projects were associated with larger discounts in the event study. |
| First facility versus an existing cluster | Whether the area already has industrial uses and data centers | The first large facility can create a bigger change in expectations; an established cluster may have effects already reflected in prices. |
| Urban versus rural setting | Existing industrial zoning, vacant land, road capacity, and nearby homes | The event study reported larger effects in urban locations, while intervening industrial uses can reduce direct exposure. |
Distance should be measured from the home to the relevant boundary or equipment, not simply from a city-center label. Map the parcel, the planned building envelope, substations, transmission lines, access roads, and any later phases shown in planning documents.
How to estimate the value effect for one house
- Establish the timeline. Record the date of the first public announcement, rezoning or permit filings, construction start, expected energization, and any approved expansion. A sale before an announcement is not a clean comparison with a sale after it.
- Define comparable distance bands. Gather recent closed sales within one mile, one to three miles, and farther away. Keep neighborhood quality, school assignment, lot size, age, condition, and renovation level as similar as possible.
- Separate industrial context. Note whether each sale is next to other warehouses, factories, quarries, rail lines, or major roads. The Fairfax summary indicates that failing to account for all industrial properties can change the result.
- Match facility characteristics. Compare projects by building size, announced power capacity, cooling design, generation equipment, and number of phases. A small edge facility is not a valid proxy for a hyperscale campus.
- Inspect lived conditions. Visit at different times, including evening and weekend. Listen for mechanical hum, observe lighting and truck movements, and check whether the home has a direct view or a wooded or industrial buffer.
- Use a qualified valuation professional. Ask an appraiser or agent to document paired or matched sales and to explain adjustments rather than applying a blanket percentage from a published study.
A published average is a starting point, not an appraisal. The 3% and 7.2% estimates describe groups of transactions under the study’s design; they do not predict the exact resale price of a particular address.
How data centers affect property taxes
The tax base can grow substantially
Data centers add high-value real property, land improvements, and business personal property such as servers, electrical systems, and cooling equipment. That can increase a jurisdiction’s assessed base and fund schools, public safety, roads, or other services. Personal-property value may depreciate under the county’s schedule, so the taxable contribution can change as equipment is replaced.
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Revenue does not equal a higher bill for every homeowner
A county can collect more from a data center while an individual homeowner’s bill stays flat, rises, or falls. Your result depends on the assessed value of your parcel, the adopted tax rate, equalization rules, special-district levies, exemptions, and the reassessment calendar. If new commercial revenue allows a tax-rate reduction or pays for services that support local demand, the household effect may differ from the facility’s gross contribution.
| Jurisdiction or study | Published figure | What it does—and does not—show |
|---|---|---|
| Fairfax County, FY2027 | $110.6 million in data-center revenue; approximately $260 on the average FY2027 homeowner’s real-estate-tax bill | The county’s estimate of average revenue incidence. Most revenue comes from business personal-property taxes on equipment that depreciates under the county schedule; it is not a forecast for every parcel. |
| Washington JLARC, eligible centers in King and Pierce counties | Taxable value rose from $239.2 million in 2022 to $350.2 million in 2025; taxes paid rose from $2.4 million to $3.55 million | Observed growth in the reviewed facilities. JLARC says it is unclear how much came from a tax preference versus routine equipment replacement or other investment. |
| Prince William County, tax year 2023 | Data centers represented 42% of commercial assessments | The share of commercial assessment attributed to data centers, not the share of a homeowner’s assessment or bill. |
Questions to ask the assessor and budget office
- What portion of the facility is real property versus business personal property, and how is each depreciated?
- Which assessment date and reassessment cycle will apply to the next tax bill?
- Are there abatements, exemptions, enterprise-zone rules, or negotiated payments in lieu of taxes?
- Which tax districts—county, municipality, school, fire, utility, or special service—levy on the parcel?
- How are new revenues allocated, and has the governing body changed tax rates or capital plans?
- Will transmission lines, substations, road widening, or water projects create assessments or special charges?
Obtain the subject property’s current assessment, the last several tax bills, and the adopted rates for every district. Then model a reassessment using the jurisdiction’s published method; do not divide a county’s total data-center revenue by the number of households and treat that quotient as your bill.
What is known about homeowners insurance
No standard data-center proximity surcharge is established
The National Association of Insurance Commissioners’ 2018–2024 market analysis does not publish an actuarial estimate showing that living near a data center, by itself, changes a homeowners-insurance premium. The National Association of Insurance Commissioners’ 2018–2024 market analysis describes local conditions driven by weather risk, rebuilding costs, claims patterns, and insurer participation; it does not list data-center proximity as a standard national rating factor.
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The Government Accountability Office says insurers generally start 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. GAO found that the average U.S. homeowners premium rose 3% after inflation from 2019 to 2024. Homes in severe or extreme wind-risk areas carried premiums about 58% higher than comparable homes in major-risk areas. Those figures describe broad insurance-market and hazard differences, not a data-center effect.
Facility-related issues can still affect an individual quote
An insurer may evaluate facts associated with a particular site rather than apply a named “data center” surcharge. Examples include a changed fire-response route, nearby high-voltage equipment, wildfire or flood exposure, construction characteristics, replacement cost, neighborhood crime, or a documented claims history. 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.
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- Request quotes from multiple insurers using the exact street address, not a ZIP-code estimate.
- Ask whether underwriting considers any facility-specific hazard, emergency-access change, utility infrastructure, noise-related claim history, wildfire, flood, wind, or fire-protection issue.
- Confirm dwelling limits, extended replacement-cost coverage, ordinance-or-law coverage, deductibles, exclusions, and separate flood or earthquake policies.
- Ask how a future expansion, road change, or loss of a nearby fire station would be handled at renewal.
- Save the quotes and underwriting answers so you can compare like-for-like limits and deductibles.
Do not infer a premium from the number of miles to a data center. Two homes at the same distance can receive different prices because of roof age, construction, claims, hazard maps, replacement cost, and insurer availability.
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A practical due-diligence checklist before you buy
Planning and physical conditions
- Read the zoning case, site plan, environmental documents, traffic study, noise limits, lighting plan, and approved expansion phases.
- Identify the nearest building wall, cooling plant, generators, substations, transmission corridors, water facilities, and truck entrance.
- Check construction hours, haul routes, road-improvement agreements, and whether mitigation requirements are enforceable.
- Visit during peak traffic, nighttime operation, and a quiet period; ask nearby residents what changed after announcement and construction.
Market evidence
- Request at least three recent closed sales in each relevant distance band and adjust for property differences.
- Compare sale dates with announcement and construction milestones.
- Look for price-per-square-foot, marketing time, concessions, and repeat-sale trends rather than relying on list prices.
- Ask whether the appraiser has considered industrial externalities and planned phases.
Taxes and public services
- Pull the parcel record, assessment history, tax rates, exemptions, and special-district charges.
- Read the latest adopted budget to see how data-center revenue is forecast and spent.
- Check for tax incentives, depreciation schedules, and pending reassessment or equalization changes.
Insurance and resale risk
- Get written, comparable quotes before the inspection or financing contingency expires.
- Verify fire-station distance, hydrant access, hazard maps, roof requirements, and carrier availability.
- Plan for resale: retain the site plans, sound studies, permits, and any disclosure documents so a future buyer can evaluate the same facts.
How to interpret the decision
A nearby data center is not automatically a deal-breaker or a benefit. A home within the closest band beside a new, high-capacity urban campus deserves a more conservative valuation review than a home several miles away behind existing industrial uses. Conversely, a project that funds services, adds employment, and has strong buffers may produce a neutral or positive experience in parts of the market.
Use three separate tests rather than one headline judgment:
- Market test: Do matched local sales show a discount after accounting for other industrial influences and timing?
- Fiscal test: What will this parcel actually pay under the assessor’s rules, tax districts, exemptions, and reassessment schedule?
- Risk-transfer test: What do insurers quote for this address, and which hazards or coverage limits explain the difference?
If any test is unanswered, make the purchase contingent on obtaining the missing record or quote. The available evidence supports careful, parcel-level analysis—not a universal percentage, tax increase, or insurance premium based solely on proximity.
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