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What a datacenter would fund in Waukesha County, WI

At default assumptions — 100 MW of critical IT, $11M/MW shell, $30M/MW of GPUs and IT equipment, no abatement — a new AI datacenter here would pay $8.0M a year in property and personal-property tax: 0.4% of everything Waukesha County, WI's local governments raise today, equal to 12% of its fire budget and 5% of its police budget. Adjust every assumption below.

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Jobs & wages

observedThis county's computing-infrastructure industry already employs 362 people across 27 establishments at an average pay of $442,295 6.32× the county's all-industries average of $69,989. (BLS QCEW, NAICS 518210 (computing infrastructure & data processing) and total-covered wages, 2024 annual averages.)

estimateA 100 MW build would employ roughly 70200 construction workers during the build and 1535 permanent operations staff.PwC/DCC impact study (IMPLAN) & US Chamber datacenter report (RIMS II) · CBRE: 50 MW build ≈ 400–600 construction workers · national coefficients — county-specific multipliers are paid BEA products and are not used

How WI taxes datacenter property

  • WI levies no tax on business tangible personal property — GPUs, servers, and facility equipment (chillers, UPS, generators) are untaxed; only the building and land are. [Wis. Stat. §70.111(28) (2023 Wis. Act 12): business TPP tax repealed effective with the Jan 1, 2024 assessment]
  • Roughly 55% of non-IT facility cost (building, land) is real property; the rest — chillers, UPS, generators, switchgear — is assessed as personal property under the treatment above. [Tax Foundation reference build ≈54/46; Va. Code §58.1-3506(A)(43); Texas CAD BPP schedules]
  • Commercial real property carries an effective rate ~1.089× the owner-occupied residential rate here, and the model scales the building tax accordingly. [Lincoln Institute 50-State Property Tax Comparison Study (for taxes paid in 2025), Appendix Table 6a: Milwaukee commercial-homestead classification ratio 1.089 (rank 38; -0.010 vs 2024). Wisconsin uniformity clause bars rate classification; the modest >1.0 ratio stems from homestead-favoring exemptions/credits (e.g., lottery and school levy credits).]
  • Datacenter equipment purchases are sales-tax exempt under Wisconsin Qualified Data Center Sales and Use Tax Exemption (WEDC-certified, 2023 Wis. Act 19) (minimum investment $50M) — Wis. Stat. 77.54(70); Wis. Stat. 238.40. [source]
  • Property-tax relief vehicle in WI: Tax Increment Financing (TIF) districts (terms negotiated per deal) — Wis. Stat. 66.1105.Wisconsin's uniformity clause (Wis. Const. art. VIII, sec. 1) precludes standard statutory property tax abatements; TIF is the operative local tool. Example: Microsoft's Mount Pleasant data center sits in the former Foxconn TID, with village incentive payments to Microsoft of ~42% of first-phase project tax revenue, capped at $5M/yr. 2025-26 legislature approved exceptions to the 12% TIF valuation cap for large data center TIDs in Port Washington and Beaver Dam. No statewide statutory abatement percentage exists.

Methodology & sources

County budgets — observed

Revenue and expenditure figures come from the US Census Bureau's 2022 Census of Governments Individual Unit File (FY2022, the latest full-coverage vintage, revision of July 2026) — the audited, unit-level record of every local government in the country. We aggregate all ~89,900 units (counties, cities, townships, school districts, special districts) to county areas. "Total local revenue" sums taxes, charges, and federal/state aid; transfers between local governments inside the same county are excluded so nothing double-counts. Function budgets are current operations plus construction for K-12 education, police, fire, and parks. FY2022 dollars are uplifted ×1.10 to current dollars (CPI-U annual average 2022→2025, BLS series CUUR0000SA0); the uplift is a documented approximation — county budgets grew at different rates.

Property tax rates — observed, residential proxy with classification adjustment

Each county's effective property-tax rate is median real-estate taxes paid ÷ median home value (American Community Survey 2023 5-year, tables B25103/B25077) — a residential rate. Where a state's commercial-vs-homestead classification ratio is well documented (statutory assessment classes, or the Lincoln Institute 50-State Property Tax Comparison Study's largest-city figures), the shell tax is scaled by that ratio; where the ratio is city-specific (Chicago, New York City) or low-confidence, no adjustment is applied and the shell tax is an understatement there.

Personal property on GPUs & IT equipment — modeled, per-state statutes

Fourteen states levy no tax on business tangible personal property (DE, HI, IL, IA, MN, NH, NJ, NY, ND, OH, PA, SD, plus Wisconsin since the 2024 repeal and Kansas for post-2006 equipment); equipment tax is zero there. Separate-rate jurisdictions use their actual rates: Virginia at Loudoun's $4.15/$100 on datacenter computer equipment with the county's own declining depreciation schedule (60%→5% floor, averaging ~32% of original cost over a 5-year refresh); DC $3.40/$100; Maryland's weighted-average local rate $3.17/$100; Kentucky's state + county tangible composite. Classification states apply their statutory TPP-to-residential assessment ratios (SC 10.5%/4%, CO 26%/6.8%, MO 33.3%/19%, AL 20%/10%, RI ~3.3×, and others), and West Virginia's statutory salvage valuation prices qualifying servers at 5% of original cost. Everywhere else the fleet is valued at a steady-state 55% of original cost — the 5-year straight-line midpoint the Tax Foundation's "State Taxation of Data Centers" study uses. Every state row carries its statute citation.

What counts as "building" vs "equipment" — the facility split

Only ~55% of a datacenter's non-IT construction cost is real property (land and building shell); the rest — chillers, UPS and batteries, generators, switchgear — is assessed as tangible personal property in practice (Tax Foundation reference build ≈ 54/46; Texas appraisal districts schedule generators and UPS as business personal property; Virginia's statute places substations, UPS, electrical plant and air handlers in the datacenter TPP class, Va. Code §58.1-3506(A)(43)). The model taxes the real share at the county's real-property rate and the equipment share under the state's TPP rules with a slower ~65% steady-state factor (10–25 year asset lives). Observed anchor: Loudoun County collected $875M from datacenters in FY2024, ~85% of it from personal property — the personal-property-heavy split this model reflects.

Sales tax on equipment — separate line, never blended

38 states have enacted datacenter sales-tax exemption programs; where one is open to a new project, the equipment sales-tax line is $0 with the program named (minimum-investment thresholds shown). Where none applies, sales tax on equipment purchases (Tax Foundation Jan-2026 state + average local rates) is annualized over the 4-year GPU refresh cycle and shown as a separate estimate — it never enters the property-tax totals or budget percentages. Programs a new project cannot currently access are treated as absent: Arizona's application moratorium (July 2026–June 2029), Ohio's June 2026 pause, Nebraska's LB 901 repeal and executive order, and Massachusetts's not-yet-open certification.

Cost assumptions — yours to change

Defaults are $11M/MW for the facility (Turner & Townsend 2025 US index: $9.5–13.3 per IT-load watt, +7–10% for liquid-cooled AI builds) and $30M/MW for GPUs and IT equipment (GB200-class racks at ~$3–3.5M per ~120 kW imply $25–38M/MW; announced frontier campuses run $35–45M/MW), on a critical-IT MW basis — cross-checked against the Tax Foundation's $1B / 32 MW reference facility. Real deals almost always carry negotiated abatements — the abatement slider defaults to 0% so the headline shows full statutory tax, and where a state has a clean statutory program (Nevada's 75% TPP abatement, Connecticut's qualified-data-center exemption, New Mexico's IRB structure, Mississippi's fee-in-lieu, South Carolina's FILOT) a one-click control applies its typical percentage, always labeled as the program default rather than any specific deal.

Electricity taxes — state revenue, shown separately

A datacenter's power bill carries its own tax stack: state sales/use tax on industrial electricity where it applies (many states exempt utility-delivered power or manufacturing use — datacenters usually don't qualify as manufacturing), utility gross-receipts or per-kWh excises embedded in rates (Pennsylvania's 59-mill gross receipts tax, Washington's 3.87% public utility tax, Illinois' electricity excise), datacenter-specific provisions (Tennessee's reduced 1.5% rate; Wisconsin's certified-datacenter electricity exemption; Minnesota's 2025 repeal; Iowa's 2025 cap) — and, first in the nation, Virginia's $0.011/kWh datacenter electricity consumption tax (July 2026–June 2028, capped $600M/yr statewide). Consumption is modeled as critical-IT MW × 8,760 h × PUE 1.25 × the state's EIA industrial price. These are predominantly state taxes, so they appear as a separate context line and never enter the county budget percentages. Local utility franchise fees are out of scope — no national dataset exists.

Jobs & wages — observed vs modeled, never blended

Employment and pay figures marked observed come from BLS QCEW (NAICS 518210, 2024 annual averages; county rows where disclosed, state fallback where suppressed) — e.g. Loudoun's computing-infrastructure industry pays $212,811 on average, 2.5× the county's all-industries wage. Construction and operations headcounts for a hypothetical build are estimates from published national coefficients (0.7–2.0 construction workers and 0.15–0.35 permanent FTE per critical-IT MW; PwC/IMPLAN and US Chamber/RIMS II studies) — county-specific multipliers are paid BEA products and are not used. The two layers carry distinct badges and never blend.

Audited top taxpayers & the homeowner counterfactual — observed floors

Where a county's own audited financial statements (ACFR statistical sections), assessor top-taxpayer reports, or bond official statements publish principal-taxpayer tables, they appear verbatim with the source linked — the highest-trust tier on the page. Summing the identified datacenter entities over the county's taxable base gives an observed floor on the datacenter share: top-10 lists truncate, only identified entities count, and Virginia tables cover real property only (computer-equipment personal property — the larger half of datacenter tax there — is extra). The homeowner counterfactual applies fixed-levy reallocation to that floor: if the datacenter share s disappeared and local governments collected the same total, every remaining bill rises by s/(1−s), applied to the county's median owner-occupied bill (ACS 2023 5-year, B25103). Because the expression only grows with s, a floor share yields a floor counterfactual — the figures read "at least." Counties whose published tables use a non-ratioable basis (taxes-paid rankings, abatement-inflated account values) show the table but no share.

Why the revenue is nearly all margin for a county

Datacenters pair enormous assessed value with near-zero service demand — no students, minimal police, fire, and road load per tax dollar. Cost-of-community-services studies (American Farmland Trust meta-analysis) find commercial/industrial property consumes ≈ $0.30 of services per $1.00 of tax paid versus ≈ $1.15 for residential — so the realistic alternative land use is typically a net fiscal drain.

Known limitations
  • Connecticut is greyed out: CT reports under 2022 planning-region FIPS that do not nest inside the county boundaries the map draws. Population-weighted apportionment is a tracked follow-up.
  • New York City's five boroughs are one consolidated government and are modeled as one area.
  • Hawaii's K-12 line is $0 locally — its schools are state-run; school equivalents there are not meaningful.
  • Some states offset local school-revenue gains with reduced state aid or recapture; school figures are gross of that offset (a per-state retention model is a tracked follow-up).
  • Estimates are flagged: any figure marked estimate names its anchor inputs. Observed government data is never blended with modeled figures.
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