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Short answer: an AI-era data center can lower, raise, or leave nearby home values unchanged. The result depends on distance, whether buyers learned about the project at announcement or opening, the facility’s size, noise and visual impacts, local job growth, and the health of the surrounding housing market. A September 2026 working paper estimates an average 3% decline within three miles of a large facility announcement and 7.2% within one mile, while a separate Realtor.com event study found no measurable price difference after facilities opened. County-level research reports higher house prices alongside employment and electricity-price increases, but that county result cannot be applied to one house.
What is the impact of living near a data center?
There is no universal “data-center effect” for residential property. Different studies measure different events and outcomes:
- An announcement can reveal future construction, traffic, substations, cooling equipment and possible noise before anything is built.
- An activation marks the point when a facility begins operating, after some of the expected impact may already be reflected in prices.
- A county-level growth measure captures jobs, tax revenue, construction and utility demand across a broad area, not the experience at a particular address.
That is why credible recent analyses point in different directions. Treat every percentage as an average for a defined sample and period, not as an appraisal adjustment for your home.
What the major studies actually found
Announcement-based estimate: a localized decline
Garrison Schlauch of UC Berkeley and Simon Greenhill of Harvard and Monash report in the September 2026 working paper Data Centers Lower Nearby Housing Values that large-data-center announcements were followed by lower nearby transaction prices. Their matched, stacked event-study design compares transactions near newly announced large facilities with observably similar areas near facilities announced later.
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| Distance from announced facility | Reported average estimate | How to interpret it |
|---|---|---|
| Within 1 mile | 7.2% lower over the following five years | Average estimate in the paper’s sample; not a forecast for every property |
| Within 3 miles | About 3% lower over the following five years | Localized average effect, with smaller estimates beyond three miles |
| Beyond 3 miles | Smaller effects reported | No universal cutoff was established |
The authors report larger estimates for hyperscale and higher-capacity facilities, urban locations, and the first large data center in an area. They also find a timing change: before 2021, prices responded mainly when facilities became operational; for more recently announced projects, effects were capitalized mostly at announcement. In other words, waiting for the building to open may miss the market’s first reaction.
The paper estimates that its calculated declines correspond to $20.6 billion in nationwide housing-wealth losses. It also reports annualized U.S. data-center construction spending above $75 billion in July 2026, 57% higher than a year earlier and nearly six times the July 2022 level. Those figures are estimates from the working paper, not official government totals.
Activation-based Realtor.com analysis: no measurable difference
Glen Morgenstern’s Realtor.com Economic Research report, dated August 11, 2026, asks a different question: what happened to prices after large facilities became active? Its event study covers 43 ZIP codes that received a large facility between 2019 and 2025. Comparison ZIP codes were matched on the previous year’s median sale price and population density; same-metro comparisons were used where possible, with state-level matches for five smaller or rural markets.
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Its market-exposure figures show how the geography of the issue is changing. Homes within five miles of a large active data center represented 0.67% of U.S. sales in 2018 and 1.5% in 2026. Realtor.com projects that more than 2% of sales will fall within five miles of an active large facility by the end of 2027; that is a projection, not an observed result. The median large facility opening in 2026 was in a place with 32 residential housing units per square mile, compared with 116 in 2017, suggesting newer projects are reaching less-dense areas.
County-level economic research: growth with higher costs
NBER Working Paper 35194, Data Centers and Local Economies in the Age of AI: A Shift–Share Approach, by Fernando E. Alvarez, David Argente, Joyce Chow and Diana Van Patten, was issued in May 2026 and revised in September 2026. It links facility data to county outcomes and uses an instrumental-variable strategy.
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The NBER abstract and the University of Chicago Becker Friedman Institute summary report positive estimates at different horizons for total employment, data-processing employment, construction employment, establishments, house prices, tax returns, adjusted gross income and wages. Electricity prices also rise in the estimates, and the study examines public-supply water withdrawals. Annual payroll responds less robustly.
A county can gain jobs and higher aggregate house prices while a home next to cooling equipment loses appeal. County estimates therefore describe broad economic channels, not the resale value of your individual lot.
Other evidence shows local variation
Alex Priest’s University of Rochester working-paper abstract analyzes Virginia air permits and ZIP-code prices with difference-in-differences and event-study methods. It describes economically small, slightly positive estimates and no evidence of large negative effects; results are similar for recent permits associated with AI facilities. Because the source is a working-paper abstract, it should not be treated as settled peer-reviewed consensus.
A Princeton repository abstract covering Virginia and Texas says estimated price and rent effects for larger facilities are consistent with a contemporaneous local-disamenity channel rather than a sustained local-demand boom. The available abstract does not provide enough detail to place its exact estimates on the same scale as the other studies.
The National Association of Realtors’ September 2026 coverage of its 2026 Data Center Impact report supplies context rather than a causal estimate. It says 92% of U.S. counties had no mapped data centers, while Loudoun and Prince William counties in Northern Virginia together contained about 19% of mapped U.S. facilities. Counties with more facilities were associated with higher home values, income and long-term job growth, but the report cautions that association is not causation. In its agent survey, 25% perceived a positive effect on nearby home values and 22% perceived a negative effect.
“Higher home values or faster price appreciation do not necessarily mean that data centers caused home values to increase.”
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That distinction is essential: areas selected for data centers may already have strong employment, infrastructure and housing demand.
Why the results conflict
| Study design | What is measured | What it can and cannot tell you |
|---|---|---|
| Schlauch and Greenhill announcement study | Transactions near newly announced large facilities, compared with areas near later-announced sites | Captures expectations and localized disamenities; working-paper estimates are averages, not appraisals |
| Realtor.com activation study | Listing and sale prices in 43 matched ZIP codes after opening | Tests post-activation price differences; excludes sale data from Texas and 11 other nondisclosure states |
| Alvarez, Argente, Chow and Van Patten | County employment, establishments, income, wages, house prices, electricity and water outcomes | Captures broad growth and cost channels; cannot identify a neighboring home’s value |
| Virginia permit study | ZIP-code prices around air-permit events | Reports small, slightly positive estimates in a working-paper abstract |
| NAR report and agent survey | County associations and professional perceptions | Useful context; neither establishes causation for a specific property |
The variables that matter for a specific home
Distance and sightlines
Risk is not a simple circle around a site. A house one mile away with a tree buffer and no view may experience less nuisance than a house farther away facing a substation, generator yard or truck entrance. The announcement study reports the largest average estimate within one mile and a smaller estimate within three miles, but it does not establish a universal boundary at either distance.
Project timing
Check four separate milestones: land-use proposal, public announcement, permits or construction, and commercial operation. A recent project may be priced at announcement, while an older market may have waited for operation. Asking only whether the center is “open” can therefore miss the relevant event.
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Large hyperscale facilities, higher-capacity sites and the first major center in a community produced larger estimates in the announcement study. Realtor.com’s large-facility definition starts at 50 megawatts of selected power capacity, but capacity alone does not describe a home’s noise, traffic or visual exposure.
Noise and equipment
Cooling systems, backup generators, substations and construction traffic can matter more than the server halls themselves. Virginia interviews summarized by JLARC describe noise as a concern near residential areas, while interviewees generally did not report home-value declines or slower sales in the areas they discussed. Those interviews are descriptive, not a national causal estimate.
Local demand and infrastructure
New construction jobs, permanent technical employment, tax receipts and suppliers can support demand. At the same time, electricity prices, water withdrawals, road congestion or utility upgrades can reduce affordability or desirability. The county-level study reports positive employment and house-price estimates alongside higher electricity prices; the balance depends on local policy and infrastructure.
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How to investigate a home near a proposed or operating facility
- Map the actual site. Use the parcel boundary, not a city name or ZIP-code centroid. Measure straight-line distance and identify the nearest residential edge, access road, substation and transmission corridor.
- Build a timeline. Search planning commission agendas, zoning cases, air permits, building permits, utility filings and public notices. Record announcement, permit, construction and activation dates separately.
- Identify the facility’s characteristics. Note stated power capacity, phased expansion, cooling method, generator count, operating hours, expected truck routes and whether it is the first large center locally.
- Inspect at multiple times. Visit during daytime construction or deliveries, evening peak operation and a weekend period. Listen from the yard, bedrooms and outdoor living areas rather than only from the street.
- Compare genuinely similar sales. Use recent local transactions with similar lot size, age, condition, school assignment, flood risk, highway exposure and distance to the facility. Do not apply the 3% or 7.2% study estimates mechanically.
- Check utility and tax documents. Ask the utility or local government whether rate cases, infrastructure charges, special assessments or tax changes are planned. County-level electricity-price effects do not prove your bill will rise, but they justify checking.
- Document sound concerns. A consumer sound-level meter may help you record conditions at different times, but no specific model or measurement protocol is established here. A meter does not determine legal compliance or predict resale value; formal compliance questions belong to the relevant regulator or a qualified acoustic professional.
- Ask for written disclosures. Request known projects, easements, planned substations, generator testing schedules and road changes from the seller and agents. Keep copies with your inspection file.
How buyers should use the research in a decision
Use the studies to set questions, not to manufacture a precise discount. A home within one mile of a newly announced hyperscale project deserves a different investigation from a home five miles away beside an established, screened facility. A project already reflected in local sales may produce no measurable post-opening difference even if the announcement initially affected prices.
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- Seek stronger comparable evidence when the project is new and nearby sales predate the announcement.
- Separate nuisance from marketability. You may personally tolerate sound or industrial views, but future buyers may not, increasing marketing time even when an appraisal shows little change.
- Do not assume jobs guarantee appreciation. County-level growth can coexist with a localized disamenity.
How sellers can prepare
Disclose known material facts according to your state’s rules and retain planning documents. Be precise about what is approved versus merely proposed. If noise is intermittent, document when it occurs rather than making an absolute claim. Price from current, comparable sales and buyer feedback; do not advertise a national study percentage as a guaranteed loss or gain.
Practical improvements can reduce buyer uncertainty: maintain landscaping that screens equipment where permitted, explain sound-insulation upgrades with invoices, and provide a clear map showing the home’s distance and sightlines. These steps cannot erase a market effect, but they make the property easier to evaluate honestly.
What the numbers do—and do not—mean
Suppose a hypothetical home would otherwise sell for $500,000. A 3% study estimate equals $15,000, and a 7.2% estimate equals $36,000. Those are arithmetic illustrations only; they are not an appraisal, do not account for the home’s exact distance or exposure, and come from a specific announcement-based sample. The Realtor.com study’s “no measurable difference” result likewise does not promise that every home will hold its value.
Study design also affects the apparent direction. Announcement research can capture anticipated nuisance before construction. Activation research may observe a market after expectations, jobs and infrastructure have already been incorporated into prices. County research can show gains from regional growth that mask losses at the immediate edge. Comparing the percentages without comparing their treatment date, geography and outcome produces a false contradiction.
Bottom line for homeowners
AI-driven data-center construction is expanding, but its effect on a home is local and conditional. The strongest recent negative estimate is a 7.2% average decline within one mile of a large announcement and about 3% within three miles over five years. A separate matched-ZIP-code study found no measurable listing- or sale-price difference after activation, while county-level instrumental-variable research found higher house prices together with employment and electricity-price effects. None of these findings is a guaranteed adjustment for your address.
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- INSTALLS IN CIRCUIT PANEL of most homes with clamp-on sensors. Supports Single phase, Single-split phase, and 2-wire systems. 3-wire systems; 3-phase, 4-wire Wye systems with earthed (TN or TT) neutral (no-Delta) are supported with an additional 200A sensor (sold separately).
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For a purchase or sale, identify the project milestone, measure the real distance, inspect noise and sightlines, verify expansion and utility plans, and rely on comparable local transactions. That process is more defensible than applying a national AI-data-center percentage to one property.
Frequently Asked Questions
Does living within five miles automatically reduce a home’s value?
No. Five miles is a reporting boundary used in Realtor.com’s sales-share analysis, not a universal valuation cutoff. Effects vary with distance, sightlines, noise, timing and local market conditions.
Are AI data centers different from older data centers for property values?
The available studies do not establish a single AI-versus-non-AI price rule. The announcement study reports larger estimates for hyperscale and higher-capacity facilities and similar results for recent Virginia permits associated with AI facilities, but those are not a universal comparison.
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Can higher county home prices prove a data center helped my house?
No. County-level increases may reflect jobs, existing growth or other factors. The NAR report explicitly cautions that higher values or faster appreciation do not necessarily mean data centers caused them.
Should I use a sound meter before buying?
You may use one to record conditions at different times, but no specific model or protocol is established here. A consumer meter cannot determine regulatory compliance or predict resale value.
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