DepreciMax STR Bonus Depreciation Market Study — Methodology (2026 Edition)
This document describes the data sources and estimation approach behind the DepreciMax STR Bonus Depreciation Market Study (2026 Edition), which estimates federal IRS §168(k) bonus depreciation potential across 197 US short-term rental markets and, for the Top 50 markets, across 1,717 individual property listings. The dataset produces prospecting-grade depreciation estimates intended to help buyers directionally identify — and weed out — properties and markets based on bonus depreciation potential. Estimates are closely calibrated against benchmark cost segregation studies on short-term rental properties, but are not a substitute for a formal engineered study, professional tax advice, or a filed return.
How did the DepreciMax Research Team select the 197 STR markets in this dataset?
Markets were selected to give US-wide coverage across the geographies and property types that dominate active short-term rental investing. Selection criteria are documented internally; no market was excluded for editorial reasons.
- Activity threshold. Every included market has documented short-term rental activity above a minimum active-listing threshold.
- Coverage. The dataset spans eight regions (lake, mountain, ski, desert, urban, beach, national-park-gateway, historic) and eight peer groups (mountain-cabin, ski-resort, desert-resort, urban-vacation, lake-waterpark, beach, outdoor-adventure, park-gateway) across 44 US states and the District of Columbia.
- Property scope. Within each market, the dataset covers single-family and condominium listings between $150,000 and $8,000,000 with at least one bedroom — the price band and property type mix that captures the vast majority of STR-suitable purchases.
- Neighborhood distinctness. Where a metropolitan area contains multiple distinct short-term rental submarkets with materially different price, land, or amenity profiles (for example, Wynwood versus Coconut Grove in Miami), each submarket is treated as its own market. Combined-label markets (for example, Sarasota / Siesta Key) share a single market entry.
What data sources power the DepreciMax STR Bonus Depreciation Market Study?
The dataset assembles inputs from five distinct classes of source:
- Property details from real-estate listing sites — filtered to single-family and condo, appropriate size and price bands, with structural details (square footage, bedrooms, bathrooms, property age where reported, structure type).
- County-specific land record data — assembled market-by-market at the county level, converted to zip-level land value ratios. Assembly is manual and market-specific because assessment practices, publication formats, and refresh cadences differ by jurisdiction.
- State §168(k) conformity classifications — sourced from state Department of Revenue publications, current as of the snapshot date. Each state is classified as full conformity (state allows the federal bonus depreciation deduction), decoupled (federal deduction is available but the state does not follow), or partial (state allows a modified version).
- Short-term rental listing activity — market-level counts of active short-term rental listings across major platforms (Airbnb, VRBO, and similar), used to size and weight each market in the national curve.
- Benchmark cost segregation studies on short-term rental properties — used to calibrate the per-listing bonus-eligible % estimation.
How does DepreciMax estimate median bonus depreciation potential for each market and listing?
Estimating bonus depreciation potential — the share of a property's purchase price that classifies as 5-year or 15-year property under IRS §168(k) — traditionally requires a formal engineered cost segregation study on the specific property, performed post-closing. That is exactly why most STR investors buy first and learn the tax outcome later.
The per-listing estimate combines three inputs:
- County-level land value data. The land component of a property's purchase price is not depreciable, so the land ratio is the single largest determinant of bonus depreciation potential per property.
- Listing-level property detail indicators. Attributes known from cost segregation practice to correlate with bonus-depreciable asset density — including property age, price per square foot, structure type, bedroom and bathroom density, and amenity signals surfaced in the listing.
- Market-specific typical feature sets. Knowledge of what is standard for short-term rental-suitable properties within each peer group. A mountain-cabin market carries a different typical amenity stack (hot tubs, decks, fireplaces, finished lower levels) than an urban-vacation market or a beach market. These typical feature sets are applied per peer group, not per property.
The output for each listing is a per-listing bonus-eligible percentage — the estimated share of purchase price that classifies as 5-year or 15-year property under §168(k). Aggregating those per-listing estimates within each market produces the market's median bonus depreciation potential, along with the market's distribution characteristics.
How are the Diamond, Gold, Silver, and Bronze market tiers defined?
Every scored listing earns a national medal based on its bonus-eligible % of purchase price. Thresholds are fixed absolute cutoffs — not relative to a cohort — and are frozen for the annual snapshot cycle.
| Medal | Bonus-eligible % threshold | What it indicates |
|---|---|---|
| Diamond | ≥ 24% | Top-tier bonus depreciation potential — properties in this band are outliers to the upside. |
| Gold | ≥ 22% | Strong bonus depreciation potential — well above the national median. |
| Silver | ≥ 20% | Above-average bonus depreciation potential. |
| Bronze | ≥ 18% | Roughly market-median bonus depreciation potential. |
| Unmedaled | < 18% | Below-median bonus depreciation potential — often driven by high land ratios or older structural stock. |
A market never earns a medal directly. Instead, each market is described by medal density — the share of its active short-term rental-suitable listings that clear each threshold. A market with high Diamond density is a market where the tax math is stacked in favor of the buyer; a market with low Diamond-and-Gold density is one where the tax math needs to be verified property-by-property.
For the Top 50 markets, medal density is estimated using statistical density estimation at the market level, informed by the per-listing distribution within each market's Top 50 sample.
Sample-size handling: for markets with 20 or more scored listings, medal density is computed empirically from the sample distribution. For markets with 1–19 scored listings, medal density is modeled from the calibrated market median (bell curve, std 3.1pp) and flagged as a small-sample estimate. For markets with zero scored listings currently available, medal density is not published.
How is this dataset calibrated against formal cost segregation studies?
Individual property estimates are closely calibrated against benchmark short-term rental cost segregation studies. The purpose of calibration is directional accuracy — helping buyers identify which markets and properties merit a closer look, and equally which should be weeded out — not to substitute for a filed number.
A formal engineered cost segregation study remains required to establish the specific IRS-defensible bonus depreciation figure that goes on a filed return. DepreciMax's contribution is upstream of that filing: providing a defensible market-level and listing-level indication of bonus depreciation potential at the point where buyers are deciding which markets to research and what offer to make on a specific property.
Calibration is reviewed each annual refresh. Where estimates drift versus benchmark studies, the estimation approach is retuned before the next snapshot is published. When search-page medal assignments and full-report bonus-eligible percentages disagree beyond a persistent margin on the same property, the case is logged for calibration review.
What are this dataset's limitations, and how should investors use it?
This dataset is designed to be genuinely useful for prospecting — and honest about what it is not. In particular:
- Estimates, not filings. Every number in this dataset is an estimate. Any bonus depreciation figure claimed on a filed return should be supported by a formal engineered cost segregation study on the specific property.
- DepreciMax is not a CPA firm. Nothing in this dataset constitutes tax advice, legal advice, or investment advice. Investors should consult a qualified CPA or tax advisor before making purchase decisions or claiming any specific bonus depreciation figure on a filed return.
- Median statistics. Market-level medians describe the middle of the distribution. Individual properties can and do vary significantly from the market median in either direction — that variability is precisely why per-listing scoring exists on the Top 50 markets and why property-level reports exist as a paid product on DepreciMax.
- Tax yield, not revenue. This dataset scores markets and listings by bonus depreciation potential, which is a component of after-tax return. It does not score revenue potential, occupancy, cap rate, or appreciation. It is designed to be used alongside — not as a substitute for — mainstream short-term rental market data.
- Snapshot date matters. This is a 2026 dataset. State §168(k) conformity, short-term rental regulations, property prices, and the federal §168(k) bonus depreciation percentage itself are subject to change. The refresh cadence is annual; each edition is stamped with a snapshot date and methodology version.
- Federal §168(k) applies only under specific conditions. The short-term rental depreciation strategy commonly discussed in this space depends on material participation and average rental period tests, among other conditions. Meeting those conditions is a matter for the taxpayer and their CPA, not for a market data provider.
How to cite this dataset
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For research inquiries, dataset excerpts, or partnership requests, contact the DepreciMax Research Team at [email protected].