Open data · CC-BY 4.0

Dallas, TX cost segregation benchmarks (2026)

Engine-derived ROI data from 5 representative Dallas-area properties. Methodology transparent below. CC-BY 4.0, journalists, CPAs, and researchers may cite this dataset with attribution.

Three key findings for Dallas

  1. Median engine-estimated Year-1 federal savings: $23,137 (interquartile range $20,805–$30,762, full range $17,334–$33,117) across 5 representative fixtures with purchase prices $425,000–$685,000. Assumptions: 100% bonus depreciation under OBBBA; 37% federal top marginal bracket. Individual property results vary substantially based on specific condition, renovation history, and rental treatment.
  2. Median reclassification ratio: 16.0% (interquartile range 15.4%–16.6%, full range 11.5%–19.6%). Furnished STRs sit higher in the range due to FF&E density; long-term rentals sit lower; renovation-cost-pool-driven properties span both. Your specific property may fall outside this range either direction depending on actual condition and renovation history.
  3. Median land allocation: 22.5% (interquartile range 21.9%–22.7%, full range 20.4%–24.3%). Resort-tier and high-cost-of-land neighborhoods (where the engine's premium land floor often applies) compress depreciable basis as a percentage of purchase price, but produce larger absolute dollar deductions. See the methodology note below the neighborhood table for the premium-floor mechanism.

Important framing: These are engine outputs for representative fixture scenarios, not predictions about any specific property. The cost segregation engine takes real property data (address, year built, square footage, renovation history, assessor records) and produces a study tailored to your actual property. The aggregate numbers shown here describe the Dallas market's general profile; your specific results will reflect your specific property.

Per-fixture results

Each fixture was run through the Cost Seg Smart engine, the same engine that produces real customer studies. Numbers below are reproducible from cities/dallas.json via scripts/run_city_stats.py.

Property Neighborhood Price Basis Land % 5-yr 15-yr Reclass % Y1 fed savings @ 37%
Bishop Arts Bungalow Flip
SFR · Built 1928
Bishop Arts / Oak Cliff $525,000 $405,668 22.7% $34,285 $28,248 15.4% $23,137
M Streets Tudor Rental
SFR · Built 1934
M Streets / Lakewood $685,000 $518,202 24.3% $47,935 $35,205 16.0% $30,762
Uptown Condo Investor
CONDO · Built 2012
Uptown / Oak Lawn $525,000 $406,718 22.5% $43,049 $3,800 11.5% $17,334
Frisco Suburban SFR Rental
SFR · Built 2009
Plano / Frisco (suburban Collin County) $425,000 $338,088 20.4% $32,769 $23,461 16.6% $20,805
Arlington Fourplex BRRRR
FOURPLEX · Built 1988
Arlington / Grand Prairie (Tarrant County, suburban) $585,000 $456,885 21.9% $62,642 $26,864 19.6% $33,117

Reclassification by property type

Engine property typeFixturesMedian reclass %MinMax
SFR 3 16.0% 15.4% 16.6%
CONDO 1 11.5% 11.5% 11.5%
FOURPLEX 1 19.6% 19.6% 19.6%

"STR" denotes residential property operating as a short-term rental, the engine applies an FF&E density uplift not captured in the LTR (long-term rental) treatment.

Typical land allocation by neighborhood

NeighborhoodTypical valueTypical land allocationProfile note
Bishop Arts / Oak Cliff $525,000 ~26% Pre-war 1920s–1940s bungalow and craftsman stock heavily renovated post-2010. Strong fix-and-flip activity. Higher land allocation due to gentrification-driven scarcity premium. Mix of fix-and-flip and SFR rental.
M Streets / Lakewood $685,000 ~30% Historic streetcar-suburb neighborhoods east of downtown Dallas. 1920s Tudor and Colonial Revival stock. Higher land allocation, established neighborhood-scarcity premium. Mix of fix-and-flip and high-end SFR rental.
Uptown / Oak Lawn $525,000 ~32% Downtown-adjacent mid-rise condo dominant. Post-2010 new construction with cleaner reclassification ratios. Higher land allocation reflecting urban-core scarcity. Mid-rise condo investor market.
Plano / Frisco (suburban Collin County) $425,000 ~22% Suburban SFR market north of Dallas in Collin County. Tech-employer-driven rental demand. Lower land allocation. Strong LTR rental cash flow. Collin County jurisdiction, separate from Dallas city regulation.
Arlington / Grand Prairie (Tarrant County, suburban) $285,000 ~18% Lower-cost SFR rental market between Dallas and Fort Worth. Lowest land allocation. Strong BRRRR and build-to-rent activity. Tarrant County jurisdiction with permissive regulation.
Why per-fixture engine output may differ from the typical land allocation:

The "typical land allocation" column reflects baseline patterns for each sub-market based on county assessor records and statistical modeling. For specific properties where reconstruction cost (RSMeans 2024 component build-up adjusted for time and geography) exceeds 2.0× the implied depreciable basis after subtracting the baseline land, the engine applies a premium land floor (~50%) to keep the study within audit-defensible territory. This typically affects ultra-premium resort inventory (ski-in/ski-out, beachfront, view-premium properties), where land scarcity premium dominates the purchase price. The per-fixture table above shows the actual land_source used by the engine for each fixture, values of statistical_premium_floor indicate the premium-floor mechanism was applied.

The takeaway: typical neighborhood allocations describe the market baseline. Individual property results depend on specific reconstruction-cost-vs-purchase-price ratios, and ultra-premium product may show higher land allocation in the engine output than the neighborhood typical.

Texas tax context

Texas state position on §168(k) bonus depreciation:

Texas has no state individual income tax, federal §168(k) bonus depreciation is the entire tax story for Dallas investors. No state addback, no decoupling math, no Schedule X reconciliation. Combined with 100% federal bonus depreciation under OBBBA, this is among the cleanest cost-seg tax positions in the country.

State income tax structure: No state individual income tax (constitutional prohibition)

Verify with your CPA. State tax conformity for federal §168(k) is adjusted frequently. Framing reflects our understanding as of May 2026, verify current-year treatment with a qualified tax professional.

Methodology

Every figure on this page is reproducible. The pipeline:

  1. Fixture definition. 5 Dallas-area properties defined in cities/dallas.json under the engine_fixtures array, each with address, property type, purchase price, year built, square footage, and STR/LTR flag.
  2. Engine run. The script scripts/run_city_stats.py instantiates a PropertyInput for each fixture and calls engine.run_study(), the same path that produces a real customer study.
  3. Base costs. RSMeans 2024 construction-cost data by component category, applied as base-rate per square foot.
  4. Time index. BLS Producer Price Index (Construction Materials series WPUFD49207) adjusts RSMeans 2024 dollars to acquisition-date dollars.
  5. Geographic factor. Six-tier resolver: pinned metros → calibrated → manual → state → region → national default.
  6. Land allocation. County assessor records when reliability gate passes; statistical fallback (metro → state → national medians) otherwise. Premium floor applies when reconciliation factor (rf_raw) exceeds 2.0.
  7. MACRS classification. IRS Pub. 946 + Rev. Proc. 87-56 asset class lives, 5-year (personal property), 7-year (office equipment), 15-year (land improvements), 27.5-year (residential structure), 39-year (commercial structure).
  8. Bonus depreciation. 100%, the One Big Beautiful Bill Act (OBBBA, signed July 2025) permanently restored 100% bonus for property placed in service in 2025 and later.
  9. Federal tax savings illustration. Computed at the 37% top marginal bracket. Actual savings vary by taxpayer; consult your CPA.

For full methodology details including QC validation, reconciliation logic, and audit-defense documentation, see costsegsmart.com/methodology.

Citation

This dataset is licensed under the Creative Commons Attribution 4.0 International License. You may republish, remix, or extend this data for any purpose with attribution. Suggested citation format:

Cost Seg Smart Research Team. (2026). "Dallas, TX Cost Segregation Benchmarks 2026." Cost Seg Smart. 5 representative fixtures.
Retrieved from https://dallascostseg.com/data/dallas-cost-seg-stats/

For interview requests, additional data slices, or related questions: [email protected].

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