What this dataset is
For each of 24 U.S. markets where Cost Seg Smart operates a market-specific resource site, we ran 5 representative property fixtures (120 total fixtures) through the same engine that produces real customer studies. Inputs include address, year built, square footage, property type, and rental treatment (STR vs LTR). Outputs include 5/7/15-year MACRS reclassification amounts, land allocation, reconciliation factor, and illustrative Year-1 federal tax savings.
The dataset captures something the existing cost-seg literature doesn't: how cost segregation outcomes vary across geographic and regulatory contexts. Same engine, same methodology, applied across markets that span no-state-income-tax (TX, FL, TN, NV, WA) → federal-conforming (CO, UT, IL with modifications) → high-tax decoupled (CA, NY, HI). The cross-market variance reveals how state tax regime, property archetype mix, and STR regulatory environment compound to produce meaningfully different effective tax outcomes for otherwise-similar investments.
Key findings
- Year-1 federal tax savings vary 5× across U.S. markets for the same engine methodology. Market medians range from $21,886 (Chicago metro LTR) to $107,473 (30A beach SFR STR). The spread reflects property archetype mix and rental treatment (STR vs LTR) more than location alone — markets with furnished short-term rental product (Park City, Breckenridge, 30A, Naples) sit at the top; metro long-term-rental markets (Dallas, Houston, Chicago, Charlotte, NYC) sit at the bottom.
- State tax regime materially affects after-tax economics — but not engine output. The cost-seg study itself (component identification, MACRS classification, basis allocation) is governed by federal tax law and is identical across states. What changes is the after-tax economics: 9 of our 24 markets are in states with no individual income tax (federal §168(k) is the entire tax-savings story), 3 markets are in fully-conforming states (federal + small state acceleration in Year 1), and 12 markets are in states that partially decouple or have addition/subtraction modifications. The state-side timing math differs even when total deduction is similar over the property's hold.
- Cross-market median reclassification ratio: 25.7% (interquartile range 16.4%–26.3%). Furnished short-term rentals in mountain-ski and Smokies-cabin cohorts cluster at the top of the range (24–32%) due to FF&E density. Long-term-rental metro markets cluster at the bottom (14–20%) where the engine doesn't apply STR FF&E uplift.
- Land allocation is the dominant variable behind market-level reclass differences. Resort-tier inventory (Deer Valley in Park City, Rosemary Beach on 30A, Wailea on Maui, Peak 8 in Breckenridge) frequently triggers the engine's premium land floor mechanism — pushing land allocation to 50%+ for the highest-value properties where reconstruction cost analysis indicates land scarcity dominates the purchase price. This compresses reclassification ratios as a percentage of purchase, even where absolute dollar deductions remain large.
- STR regulatory restrictions show up in the data. Three markets in our dataset — NYC (Local Law 18), Los Angeles (Home-Sharing Ordinance), and Maui (post-Lahaina STR phase-out) — face material restrictions on absentee STR operation. These markets show narrower reclassification ranges with lower medians because the engine treats restricted-STR-property fixtures as LTR (no FF&E uplift). The honest reading: cost segregation still works in restricted-STR markets, but only for LTR-positioned investments.
Why markets cluster the way they do
Before reading the per-market table, it helps to understand which structural factors produce which Year-1 federal tax savings band. The 24 markets in this dataset cluster into seven bands defined by property archetype mix, rental treatment, and state tax position — not by geography alone.
| Market band | Typical reclass % | Typical Y1 savings | Why this band |
| Dense urban metro (LTR-dominant) | 12–17% | $20K–$35K | Engine doesn't apply STR FF&E uplift to long-term-rental properties. Pre-war/post-war metro stock has lower per-square-foot land improvement density than newer construction. STR ordinances in most large metros (Local Law 18 in NYC, Home-Sharing Ordinance in LA, Seattle's STR limits, Chicago's Shared Housing Ordinance) restrict the §469 STR-loophole strategy structurally. |
| Metro + STR hybrid (mixed strategies) | 14–18% | $30K–$45K | Metro markets with adjacent STR feeder potential (LA's Burbank/WeHo neighbors, Denver's mountain proximity). Fix-and-flip + ADU + small MF investor profile dominates with limited STR fixture exposure. |
| Mid-tier mountain + cabin STR | 22–24% | $40K–$55K | Furnished cabin STR product with strong FF&E density (sleeps-12+ family-vacation layouts, decking, fire pits, hot tubs). Mid-tier price points ($400K–$700K) produce moderate absolute basis. State tax position varies (TN no-tax for Gatlinburg/Pigeon Forge; OK partial for Broken Bow; NC partial for Asheville). |
| Historic urban STR | 22–25% | $45K–$55K | 1800s structural shells reclassify poorly, but post-2000 renovation pools drive 60–75% of accelerated reclassification. Renovation cost-seg is the load-bearing mechanism. Historic-preservation review premiums on renovation cost can compound favorably. |
| Desert STR | 23–24% | $35K–$67K | Wide dispersion driven by sub-market heterogeneity — Sedona view-premium properties run high land allocation (32–38%) compressing reclass percentage but producing large absolute deductions; Las Vegas master-planned community product runs lower land allocation with cleaner ratios. |
| Mountain ski-resort STR | 21–23% | $38K–$99K | Furnished ski-resort product with substantial FF&E density. Wide variance driven by resort-tier vs off-mountain product mix — Park City Deer Valley and Breckenridge Peak 8 trigger the engine's premium land floor (~50%) at high basis levels, producing very large absolute deductions despite compressed reclass percentages. |
| Luxury coastal STR (the variance leaders) | 23–28% | $59K–$107K | Highest dispersion in the network. Luxury beachfront SFR + New Urbanist beach-cottage stock (Seaside, Rosemary Beach, Alys Beach on 30A; Old Naples and Park Shore on Naples) combines large basis, high FF&E density for furnished vacation rentals, and view-premium land allocation. 30A specifically is the network's high-end outlier — high-quality, well-located Gulf inventory often produces $100K+ Year-1 deductions. |
Reading the table that follows: the 5× spread between the lowest-Y1 market (Chicago, $21,886) and the highest (30A, $107,473) is not random. It reflects the underlying band structure above. Chicago is dense-urban metro LTR with no STR FF&E uplift and IL's IITA Schedule M modifications spreading the state-side benefit; 30A is luxury coastal STR with high FF&E density on $1.5M+ basis and Florida's no-state-tax position. The two markets are economically different even though both run on the same engine.
Per-cohort breakdown
The 24 markets group into 8 cohorts that share property archetype and demand drivers. Cohort assignment governs how the engine treats FF&E density, land allocation patterns, and rental-mode interpretation:
| Cohort | Markets | Median Y1 savings | Median reclass |
| Metro investor | Seattle, Charlotte, New York City, Dallas, Houston, Chicago | $27,167 | 16.2% |
| Metro + STR hybrid | Los Angeles, Denver | $43,063 | 16.4% |
| Coastal STR | 30A, Naples, Maui, Destin | $72,412 | 26.6% |
| Mountain ski STR | Breckenridge, Park City, Bozeman, Big Bear | $90,760 | 26.1% |
| Mountain cabin STR | Tahoe, Broken Bow, Asheville | $44,678 | 25.9% |
| Smokies cabin STR | Gatlinburg, Pigeon Forge | $47,298 | 26.7% |
| Desert STR | Sedona, Las Vegas | $66,993 | 26.3% |
| Historic urban STR | Savannah | $47,117 | 22.6% |
State tax regime breakdown
One of this dataset's most useful contributions is showing how state tax regime interacts with federal §168(k) acceleration. We classify each market into three categories:
| Regime | Markets in dataset | Cost-seg framing |
|---|
| No state income tax (9) | Seattle, Dallas, Houston, 30A, Naples, Destin, Las Vegas, Gatlinburg, Pigeon Forge | Federal §168(k) at 100% under OBBBA is the entire tax-savings story. Cleanest possible state position. States: TX, FL, TN, NV, WA. |
| Federal-conforming with state income tax (3) | Denver, Breckenridge, Park City | Federal §168(k) acceleration flows through to state return without addback. Both federal and state liability reduced in Year 1. States: CO, UT. |
| Decoupled or partially decoupled (12) | Los Angeles, Charlotte, New York City, Chicago, Maui, Sedona, Tahoe, Broken Bow, Asheville, Bozeman, Big Bear, Savannah | Federal §168(k) Year-1 acceleration captures, but state-side benefit is partially or fully deferred over the regular MACRS schedule. States: CA, NY, IL, NC, GA, OK, AZ, MT, HI. |
Verify with your CPA. State tax conformity for federal §168(k) bonus depreciation is adjusted frequently — multiple states have modified treatment two or more times in the past decade. The framing above reflects our understanding as of 2026-05-15. Always verify current-year treatment with a qualified tax professional before relying on specific dollar projections.
Top 5 markets by Year-1 federal tax savings
Highest engine-estimated Year-1 federal tax savings (100% bonus, 37% top bracket) across our 24-market dataset. These are the markets where the combination of furnished STR positioning, property archetype, and basis level produces the largest absolute Year-1 deductions:
| Rank | Market | Cohort | Y1 median savings | Reclass median | Detail |
|---|
| 1 | 30A, FL | Coastal STR | $107,473 | 27.2% | 30acostseg.com → |
| 2 | Breckenridge, CO | Mountain ski STR | $98,934 | 26.1% | breckenridgecostseg.com → |
| 3 | Park City, UT | Mountain ski STR | $90,760 | 26.1% | parkcitycostseg.com → |
| 4 | Naples, FL | Coastal STR | $72,412 | 26.3% | naplescostseg.com → |
| 5 | Sedona, AZ | Desert STR | $66,993 | 26.3% | sedonacostseg.com → |
Top 5 markets by reclassification ratio
Highest engine-observed reclassification ratios (5/7/15-year amounts as a percentage of depreciable basis) across our 24-market dataset. These are the markets where the engine's component analysis identifies the largest share of basis as eligible for accelerated MACRS treatment — a function of FF&E density, renovation cost pool, and land allocation:
| Rank | Market | Reclass median | IQR | Y1 savings median |
|---|
| 1 | 30A, FL | 27.2% | 26.9% – 27.7% | $107,473 |
| 2 | Gatlinburg, TN | 26.7% | 25.9% – 27.0% | $47,298 |
| 3 | Maui, HI | 26.6% | 26.4% – 26.9% | $62,694 |
| 4 | Naples, FL | 26.3% | 26.2% – 27.0% | $72,412 |
| 5 | Destin, FL | 26.3% | 25.5% – 27.5% | $59,164 |
Three markets that deserve specific context
Three markets in the dataset warrant extra framing because their numbers are easy to misread:
30A — the network's hero outlier
30A ($107,473 median Y1, 24.9% reclass) sits at the top of every aggregate metric in this dataset and is easy to mentally anchor on. It shouldn't be. The 30A number reflects a specific combination: luxury beachfront SFR ($1.5M–$2.85M basis), high FF&E density typical of furnished vacation rental product, New Urbanist beach-cottage architecture, and Florida's zero state income tax. Comparing a $107K 30A median to a $22K Chicago median is comparing two different investment products — not two different ROI levels for the same product. The same investor with the same budget cannot choose between "Chicago at $22K" and "30A at $107K"; the underlying property profiles, basis levels, and rental treatments are categorically distinct.
Naples — wide variance is genuine
Naples shows an unusually wide IQR ($34K–$104K) because the city contains genuinely heterogeneous sub-markets: Old Naples luxury condo ($1.85M+, mid-rise gulf-front), Pelican Bay master-planned villa ($985K resort community with HOA capital-assessment exposure), Park Shore gulf-front condo ($1.325M with 30%+ land allocation), East Naples inland LTR ($425K standard single-family rental), and Bonita Springs Lee County (separate jurisdiction with master-planned community SFR STR). These are five different product types in the same "Naples" label — the wide variance reflects real economic heterogeneity, not engine instability.
NYC — this market often does NOT pencil
NYC ($27,167 median Y1, 14.5% reclass) sits at the lower end of the dataset and we want to be explicit about why. Local Law 18 effectively eliminated absentee short-term rental operation in NYC. The §469 STR-loophole strategy that drives high reclassification on cities like Joshua Tree, Tahoe, Park City, and Gatlinburg is structurally unavailable for typical NYC investors. Combined with NY state + NYC local income tax reaching ~14.8% combined top marginal — and NY's partial decoupling from federal §168(k) — the after-tax math on NYC cost segregation often does not pencil for the typical investor profile that pencils elsewhere. The federal Year-1 deduction is still real; the multi-year operating economics around it are materially less attractive than in TX/FL/TN/NV markets at similar property basis levels. We list NYC in this dataset for completeness and to be honest about the math — not because we think most investors should buy NYC property specifically for cost-seg purposes.
The same honest-downside framing applies in lighter form to LA (Home-Sharing Ordinance), Maui (post-Lahaina STR phase-out), Seattle (STR ordinance restricting absentee operation), and Chicago (Shared Housing Ordinance). Cost segregation works in these markets — but the §469 STR-loophole path that drives the highest reclassification ratios elsewhere is restricted or unavailable.
Full per-market table
All 24 markets sorted by cohort then by median Year-1 savings. Each market has a dedicated resource site with deeper engine output, neighborhood breakdown, regulatory context, and FAQ:
| Market | Cohort | State tax | Y1 median | Y1 IQR | Reclass median | Land median |
| Los Angeles, CA | Metro + STR hybrid | Decoupled / partial, Up to 13.3% (top marginal) | $43,063 | $39K–$54K | 16.3% | 42.7% |
| Denver, CO | Metro + STR hybrid | Federal-conforming, 4.40% (flat) | $32,517 | $30K–$35K | 16.4% | 28.5% |
| Seattle, WA | Metro investor | No state income tax | $31,514 | $28K–$34K | 16.2% | 39.4% |
| Charlotte, NC | Metro investor | Decoupled / partial, 4.5% (flat, declining to 3.99% over coming years) | $30,055 | $21K–$41K | 16.4% | 18.8% |
| New York City, NY | Metro investor | Decoupled / partial, Up to 10.9% NY state + up to 3.876% NYC additional (combined up to ~14.8% top marginal) | $27,167 | $27K–$46K | 16.0% | 34.3% |
| Dallas, TX | Metro investor | No state income tax | $23,137 | $21K–$31K | 16.0% | 22.5% |
| Houston, TX | Metro investor | No state income tax | $22,710 | $21K–$25K | 16.3% | 19.7% |
| Chicago, IL | Metro investor | Decoupled / partial, 4.95% (flat) | $21,886 | $21K–$27K | 16.0% | 24.7% |
| 30A, FL | Coastal STR | No state income tax | $107,473 | $93K–$108K | 27.2% | 27.2% |
| Naples, FL | Coastal STR | No state income tax | $72,412 | $52K–$94K | 26.3% | 24.5% |
| Maui, HI | Coastal STR | Decoupled / partial, Up to 11% (progressive) | $62,694 | $52K–$82K | 26.6% | 44.5% |
| Destin, FL | Coastal STR | No state income tax | $59,164 | $49K–$86K | 26.3% | 26.1% |
| Sedona, AZ | Desert STR | Decoupled / partial, 2.5% (flat) | $66,993 | $63K–$87K | 26.3% | 21.6% |
| Las Vegas, NV | Desert STR | No state income tax | $38,536 | $34K–$50K | 25.1% | 22.4% |
| Tahoe, CA/NV | Mountain cabin STR | Decoupled / partial, CA up to 13.3% (south + west shore) · NV 0% (north + east shore) | $55,694 | $49K–$90K | 25.9% | 36.3% |
| Broken Bow, OK | Mountain cabin STR | Decoupled / partial, 4.75% (top marginal) | $44,678 | $41K–$47K | 26.2% | 13.7% |
| Asheville, NC | Mountain cabin STR | Decoupled / partial, 4.5% (flat, declining to 3.99% over coming years) | $42,984 | $38K–$44K | 23.4% | 18.6% |
| Breckenridge, CO | Mountain ski STR | Federal-conforming, 4.40% (flat) | $98,934 | $79K–$104K | 26.1% | 23.3% |
| Park City, UT | Mountain ski STR | Federal-conforming, 4.65% | $90,760 | $72K–$110K | 26.1% | 23.8% |
| Bozeman, MT | Mountain ski STR | Decoupled / partial, Up to 5.9% (top marginal, after 2024 reform) | $65,712 | $37K–$75K | 25.4% | 17.4% |
| Big Bear, CA | Mountain ski STR | Decoupled / partial, Up to 13.3% (top marginal) | $37,768 | $29K–$42K | 26.1% | 34.4% |
| Gatlinburg, TN | Smokies cabin STR | No state income tax | $47,298 | $38K–$48K | 26.7% | 20.3% |
| Pigeon Forge, TN | Smokies cabin STR | No state income tax | $43,474 | $33K–$45K | 26.3% | 20.3% |
| Savannah, GA | Historic urban STR | Decoupled / partial, 5.49% (flat) | $47,117 | $39K–$50K | 22.6% | 17.6% |
Methodology
Every figure in this dataset is reproducible. The pipeline:
- Fixture definition. Each market has 5 representative property fixtures defined in
cities/{slug}.json, with address, property type, purchase price, year built, square footage, and STR/LTR flag selected to span the market's primary sub-market profiles. - Engine run. Each fixture is run through the Cost Seg Smart engine — the same path that produces real customer studies — via
scripts/run_city_stats.py. - Base costs. RSMeans 2024 construction cost data by component category.
- Time index. BLS Producer Price Index (Construction Materials, series WPUFD49207) adjusts RSMeans 2024 dollars to acquisition-date dollars.
- Geographic factor. Six-tier resolver: pinned metros → calibrated → manual → state → region → national default.
- Land allocation. County assessor records when reliability gate passes; statistical fallback otherwise. Premium land floor (~50%) applies when reconciliation factor (rf_raw) exceeds 2.0.
- MACRS classification. IRS Pub. 946 + Rev. Proc. 87-56.
- Bonus depreciation. 100% under OBBBA (permanently restored, 2025+).
- Federal tax savings illustration. Computed at 37% top marginal bracket. State-side reconciliation handled per each state's specific conformity rules.
Full engine methodology: costsegsmart.com/methodology.
Important framing
- These are engine outputs for representative fixture scenarios — not predictions about any specific property. The engine takes real property data (address, year built, square footage, renovation history, county assessor records) and produces a study tailored to your actual property. Aggregate numbers describe market profiles; your specific results reflect your specific property.
- Year-1 federal tax savings is illustrative at the 37% top marginal bracket. Actual savings depend on the taxpayer's marginal bracket, passive vs active treatment under §469, real-estate-professional status, and other factors. Consult a qualified tax professional for advice specific to your situation.
- State tax conformity is verified as of publication date but adjusted frequently. Multiple states have modified treatment two or more times in the past decade. Always verify current-year rules with a qualified CPA before relying on specific dollar projections.
- STR regulatory environments are evolving. Markets noted as having active STR restrictions (NYC, LA, Maui, Seattle, Chicago) face hold-period uncertainty that should be modeled into multi-year underwriting.
Citation
This dataset is licensed Creative Commons Attribution 4.0 International. Republication is permitted with attribution. Suggested citation:
Cost Seg Smart Research. (2026). "STR Cost Segregation Benchmarks by U.S. Market (2026): Engine-Derived Analysis of 120 Sample Studies Across 24 Markets." Retrieved from https://costsegsmart.com/research/str-benchmarks-by-market-2026/
For interview requests, custom data slices, or methodology questions: support@costsegsmart.com.
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