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Primary Market Area (PMA) Definition in Feasibility Studies: How Institutional Reports Quantify the Geographic Boundary of Demand

  • 23 hours ago
  • 16 min read

1. Why PMA Decides Feasibility

The Primary Market Area is the single most consequential analytical decision in any feasibility study. Every other input — demand projection, capture rate, competitive supply, absorption schedule, achievable rents — is derivative of the geographic boundary the analyst draws around the subject. A defensible PMA produces a defensible feasibility conclusion. An indefensible PMA invalidates everything downstream.


The PMA carries this much weight because feasibility is a multiplicative calculation. Demand equals (qualified households or visits in the PMA) × (penetration or capture rate). Both terms scale with the boundary. Expand the PMA by 20%, and aggregate qualified demand expands roughly 20%, which mechanically lowers the implied capture rate against the same supply. Reviewers know this. Every state housing finance agency, every SBA lender, every USDA reviewer, every CMBS underwriter checks the PMA first.


A study that opens with an undisclosed methodology for PMA boundary selection has already failed the review before any number is read.


The discipline of institutional feasibility is therefore the discipline of PMA construction. The remainder of this paper sets out the four regulatory anchors, the four construction methods, the asset-class conventions, the three-tier architecture, the defensibility checklist, the data provider ecosystem, and the eight common failure modes that institutional reviewers test against.



2. Four Regulatory Anchors

Four published regulatory and standards documents establish the institutional framework within which PMA definition operates. A fifth — NCHMA — is the methodology overlay for affordable rental housing.


SBA SOP 50 10 8 (effective June 1, 2025) (1) is the operative procedural standard for SBA 7(a) and 504 lending. It supersedes SOP 50 10 7.1 and applies to all loans receiving an SBA loan number on or after June 1, 2025. The SOP requires that feasibility studies for SBA-financed projects be prepared by independent third-party consultants and that the studies address market analysis on a basis consistent with the loan's underwriting framework. The SOP does not codify a single page-numbered PMA construction rule, but the operative independence standard for third-party feasibility studies is implicit in general SBA underwriting requirements.


USDA 7 CFR Part 5001 (2), the OneRD Guaranteed Loan Regulation, is the federal rule governing Business & Industry (B&I), Community Facilities (CF), Water & Waste Disposal (WWD), and Rural Energy for America Program (REAP) guaranteed loans. §5001.3 defines a "feasibility study" as one prepared by independent qualified consultants. Appendix A to Subpart D codifies the five-component framework: economic, market, technical, financial, and managerial. The market component requires explicit PMA definition.


USPAP Standards Rule 1-3 (3), 2024 Edition (effective January 1, 2024), requires the appraiser to identify and analyze market area trends and economic supply and demand affecting the use and value of the subject property. SR 1-3 establishes the institutional standard for market area identification within real estate appraisal practice, and by extension within feasibility-related appraisal work.


Appraisal Institute, Dictionary of Real Estate Appraisal, 8th Edition (4) is the current authoritative lexicon for appraisal terminology including PMA, market area, neighborhood, and trade area definitions. The 8th edition supersedes the 7th. The Appraisal Institute itself explicitly states that professionals should rely on the most recent edition for appraisal reports, expert testimony, and current standards guidance.


NCHMA Model Content Standards, Version 3.1 (5) (updated September 2025) establishes content and methodology requirements for LIHTC and other rental housing market studies. NCHMA does not impose numeric capture-rate ceilings. Capture-rate ceilings (commonly 10–12% for family LIHTC, varying by state) are state-HFA conventions codified in QAPs, not NCHMA standards.


The institutional convention is that a feasibility study cites the regulatory anchor that binds its loan program. SBA-financed studies cite SOP 50 10 8. USDA studies cite 7 CFR Part 5001. Appraisal-adjacent studies cite USPAP. LIHTC studies cite NCHMA and the applicable state HFA QAP. A study that fails to name its regulatory anchor has not declared the standard against which it expects to be reviewed.


3. Four Methods and a Worked Huff Example

Institutional PMA construction uses four distinct methods, each appropriate for different asset types and demand patterns.



Method 1: Concentric Rings. A radius drawn from the subject site. Used where demand is approximately uniform across distance: convenience retail, self-storage, neighborhood goods. ICSC's January 2017 U.S. Shopping-Center Classification and Characteristics (6) establishes the ring convention for retail. Strengths: simple, transparent, easy to audit. Weaknesses: ignores barriers (rivers, highways, jurisdictional lines), ignores accessibility differentials, ignores demand asymmetries.


Method 2: Drive-Time Isochrones. Polygons drawn at fixed travel times (10, 15, 20, 30 minutes) using street networks. Default for restaurant, urgent care, senior living, fitness, and any asset class where access is the binding constraint. Senior living conventions per NIC MAP Vision: Independent Living ~10 mile or 15-minute drive; Assisted Living 5–7 mile; Memory Care 7–10 mile; CCRC 10–15 mile; SNF county or Hospital Service Area. Strengths: respects accessibility, captures barrier effects naturally, more behaviorally accurate than rings. Weaknesses: methodologically more opaque, sensitive to street-network data quality, requires explicit time-of-day assumptions.


Method 3: ZCTA and Census Tract Aggregation. PMA built from a list of ZIP Code Tabulation Areas or census tracts whose residents demonstrably patronize the subject. Used in LIHTC market studies (where state HFAs typically require census-tract boundaries) and in any analysis where ACS demographic precision is the binding constraint. Strengths: aligns natively with ACS, LEHD, and HUD income limits; produces clean qualified-pool counts; satisfies most state HFA QAP requirements. Weaknesses: census geography rarely matches the actual draw geography precisely; creates boundary artifacts where tracts straddle barriers.


Method 4: Gravity (Huff) Models. Probabilistic PMA construction that allocates households to competing destinations based on size and distance. The foundational paper is Huff (1964) (8), which assigns each consumer a probability of patronizing each competing destination, with probability proportional to destination attractiveness (typically GLA) and inversely proportional to distance raised to a friction exponent λ. Predecessor literature includes Reilly (1931) Law of Retail Gravitation (9) and Converse (1949) New Laws of Retail Gravitation (10).


Huff Worked Example

Subject: 200,000 SF community retail center. Competitor 1: 500,000 SF center, 6 miles distant. Competitor 2: 350,000 SF center, 4 miles distant. Friction exponent λ = 2.

Consumer at 2 miles from subject:

  • Subject attraction: 200,000 / 2² = 50,000

  • Competitor 1: 500,000 / 6² = 13,889

  • Competitor 2: 350,000 / 4² = 21,875

  • Total attraction: 85,764

  • Subject capture probability: 50,000 / 85,764 = 58.3%

Consumer at 4 miles from subject:

  • Subject: 200,000 / 4² = 12,500

  • Competitor 1: 500,000 / 6² = 13,889

  • Competitor 2: 350,000 / 4² = 21,875

  • Total: 48,264

  • Subject capture probability: 12,500 / 48,264 = 25.9%

The PMA boundary in a Huff framework is the locus of points where subject capture probability falls below a threshold (commonly 25–30% for retail). The Huff approach produces irregular boundaries that respect competition and distance, but it requires a defensible competitor set and a defensible friction exponent. Both are contestable in review.



Method selection is the first analytical decision in PMA construction and the one most often left undefended. A study that defaults to one method regardless of asset class is not following any of them.


4. Asset-Class Conventions

PMA construction is asset-class specific. The convention library is well-established for the major institutional asset types.


Retail centers follow ICSC (6, 7). Primary trade area is defined as the geographic area from which 60–80% of sales originate. By center type: Neighborhood Center 3 mile primary trade area; Community Center 3–6 miles; Power Center 5–10 miles; Regional Mall 5–15 miles; Super-Regional 5–25 miles; Lifestyle 8–12 miles. ICSC's own disclaimer (verbatim): the distances are "intended to be only typical of general features, rather than covering all situations."

Multifamily market-rate follows the 10–20 minute commute-shed convention in suburban markets and 1–2 mile radius in urban core. CoStar and Yardi Matrix data anchor competitive supply.

LIHTC follows state HFA QAPs. NCHFA (North Carolina) prohibits Secondary Market Areas entirely (2025 QAP Appendix A §II.D, verbatim: "Secondary market areas are not permitted for purposes of calculating demand") (13). TDHCA (Texas) 10 TAC §11.303 (2025 QAP) requires PMA defined by the Market Analyst using identifiable boundaries — census tracts are the standard, but ZIP codes, jurisdictions, or street-line geography are accepted; irregular shapes are permitted. The operative TDHCA convention is that PMA base-year population not materially exceed approximately 100,000 persons (14). MHDC (Missouri) 2024 Market Study Guidelines require PMA boundaries to be "a function of or agglomeration of census tracts" with narrative using "market specific language rather than a list of generic concepts or factors considered" (16). VHFA (Vermont) Market Study Standards §I.C.1 permit Secondary Market Areas only "infrequently" and require explicit deduplication math against PMA in-migration; VHFA Standards do not define a separate Tertiary Market Area construct (15).

Capture-rate ceilings for LIHTC are state HFA conventions, typically 10–12% for family product, codified in individual QAPs (NCHFA, MHDC, IHDA, TDHCA, and others). NCHMA Model Content Standards do not impose numeric capture ceilings.

Senior living follows NIC MAP Vision conventions. NIC MAP Vision coverage now spans 214 CBSAs total (31 Primary, 68 Secondary, 41 Additional, 74 Expansion 2026 markets) and tracks 35,000+ properties (11). Feasibility-study penetration ceilings of 10–12% (IL), 6–8% (AL), and 1–2% (MC) apply to income-qualified 75+ households — a narrower denominator than NIC MAP Vision occupied penetration against all 75+ households (IL ~4.0%, AL ~3.9%, MC ~1.4%) (12). Always disclose denominator. A feasibility study that quotes 10% penetration without naming the denominator is methodologically indefensible in peer review.

Self-storage uses the three-mile ring convention with isochrone validation. U.S. saturation has moved meaningfully since 2020. Current published figures: ~7.8 NRSF/capita (Yardi Matrix, January 2026) (27); 6.32 SF/capita (Self-Storage Almanac 2024) (29); 9.5 SF/capita N. America (SSA Industry Data Report 2025) (28). Metro-level dispersion is wide — under-supplied metros at 2–4 SF/capita; saturated metros at 11–16+ SF/capita. Cite the underlying source by name; the three sources diverge by ±50% on methodology.

Hospitality follows STR (CoStar Hospitality) competitive set construction. STR Competitive Set Guidelines (effective January 1, 2017): minimum 4 participating properties (excluding subject), minimum 3 unaffiliated with subject, minimum 2 unaffiliated companies, no single property or brand >50% of participating room supply, no single company (parent/operator/owner) >70%. Noncompliant sets have a 90-day cure window before data suppression (25).

Short-term rental uses AirDNA listing-level data covering 10M+ Airbnb and Vrbo listings across 120K global markets, supplemented by partner property and channel-manager feeds on approximately 1M partner properties. AirDNA applies a proprietary Booked-vs-Blocked machine-learning model using 16 booking signals with cross-platform de-duplication. Refresh cadence is daily on scrape, monthly on market aggregation (26).

Industrial labor analysis uses Census LODES (Longitudinal Employer-Household Dynamics, Origin-Destination Employment Statistics). Current vintage LODES 8.3, reference year 2022, released by Census on November 19, 2024 — a release lag of approximately 22–24 months (19, 20). LODES8 uses 2020 census blocks. Coverage gaps persist for Alaska (2017+), Mississippi (2019+), and Michigan (2022). Supplement with BLS QCEW (33) in fast-changing markets.

Hospital and healthcare uses the Dartmouth Atlas of Health Care Hospital Service Areas (HSAs) and Hospital Referral Regions (HRRs). The Atlas defines 3,436 HSAs (local primary-care markets) and 306 HRRs (regional tertiary-care markets) based on Medicare claims patterns (18). Boundaries reflect mid-1990s referral patterns and have not been periodically refreshed; disclose this vintage caveat.

Convenience retail (gas stations, c-stores, car washes, drive-thru coffee) follows a 1–2 mile or 5-minute drive convention. C-store benchmarks anchor to NACS State of the Industry data (~1,100 customers per day). Express car wash siting commonly references the 15,000–25,000 AADT industry rule of thumb; the figure is widely used but not codified by ICA or comparable authority.

Destination assets (resorts, casinos, theme parks, major sports venues) do not have a meaningful radius PMA. The PMA is defined by feeder-market origin data — where the guests, players, or visitors actually come from. STR origin data, AirDNA, or proprietary booking records anchor the analysis. A destination asset that defaults to a radius PMA has effectively conceded the geography.



5. PMA, SMA, TMA: Three-Tier Architecture

Institutional market studies allocate demand across a three-tier geographic architecture: Primary Market Area (PMA) capturing 60–80% of demand, Secondary Market Area (SMA) capturing 15–30%, and Tertiary Market Area (TMA) capturing 5–10%. The bands derive from ICSC primary-trade-area definitions and NCHMA practice.


The three-tier architecture is not universally recognized across regulators. NCHFA prohibits SMA entirely for LIHTC demand calculation (13). VHFA permits SMA only "infrequently" and does not define a separate Tertiary Market Area construct (15). Most state HFAs do not recognize a separate TMA tier — reviewers expect far-field demand to be addressed via SMA with deduplication math, not a third tier.


The discipline is to allocate demand explicitly across tiers, deduplicate against in-migration counts, and disclose the methodology. A study that aggregates demand from PMA + SMA + TMA without deduplication is double-counting households, and the reviewer will catch it.

Three operative profiles are common in practice:

  • Tight profile (75/20/5): used where the asset draws a high share locally — neighborhood retail, urban convenience, suburban multifamily within a constrained submarket.

  • Standard profile (70/22/8): the default for most institutional asset classes, anchored to the ICSC primary-trade-area band.

  • Extended profile (62/28/10): used where the asset has destination characteristics or where competing supply is far-field — luxury hotels, regional malls, premium senior living, specialized healthcare.


The choice of profile is itself an analytical decision and must be defended. A senior-living study claiming 60% PMA capture and 30% SMA capture for a non-destination CCRC is signaling that the property has a far weaker local draw than convention would predict, and the reviewer will want supporting Resident Origin data.



6. Defensibility Checklist

A defensible PMA carries a small number of specific disclosures. The institutional review of any feasibility study tests against these items. The following 12-item checklist captures the operative review criteria.


1. Boundary method named. Rings, drive-time, ZCTA, gravity, HSA, feeder market, or LODES — named explicitly, defended on first principles for the asset class. Not chosen by convention or convenience.

2. Construction inputs visible. Drive-time isochrone parameters (time-of-day assumptions, network source). Ring radius justified. ZCTA list enumerated. Gravity model exponent and competitor set named.

3. Asset-class convention cited. ICSC for retail, NIC MAP Vision for senior living, NCHMA Model Content Standards Version 3.1 for LIHTC methodology, state HFA QAP for LIHTC capture ceiling, Dartmouth Atlas for hospital. Deviations explained, not hidden.

4. Barrier and asymmetry treatment. Major barriers (highways, rivers, jurisdictional lines, school district boundaries) addressed in the boundary geometry. PMA does not arbitrarily cut through barriers.

5. Demographic vintage current. ACS 5-year vintage cited. ArcGIS Tapestry version (60 segments, June 2025) (21) or Claritas PRIZM Premier (68 segments, 2023 Narratives) (22) release date disclosed. Vintage within the institutional 18-month recency window relative to report date.

6. Capture or penetration rate explicitly bounded. Bounded against state HFA QAP for LIHTC (typically 10–12% capture). Segment-level penetration ceilings for senior living derived from NIC MAP Vision occupied penetration rates against income-qualified 75+ households. Not bounded against a generic feasibility threshold.

7. Deduplication math shown. Where SMA is invoked, explicit deduplication against PMA in-migration counts. Aggregate demand does not exceed actual qualified pool.

8. Competitive supply enumerated. Each competing property listed with name, address, unit/SF count, vintage, and basis for comp-set inclusion. STR Competitive Set Guidelines (25) followed for hospitality: min 4 properties, min 2 unaffiliated companies, no brand >50%, no operator >70%.

9. Origin data referenced where available. Resident Origin (senior living, multifamily), Placer.ai or Advan mobility patterns (retail, hospitality), STR origin data (lodging), AirDNA partner feeds (short-term rental). Origin data overrides the heuristic 70/30 PMA/SMA split where available.

10. Pipeline supply disclosed. Properties under construction, in lease-up, or in state HFA application pipeline within the prior two rounds. Pipeline omission is a common reviewer flag.

11. Vintage caveats stated. LODES release lag (22–24 months). Dartmouth Atlas vintage (mid-1990s referral patterns). ACS margins of error at block-group level (commonly 15%+ for income variables).

12. Methodology source line. Every quantitative claim traceable to a named source with date of consultation. Premium-panel claims reconciled to public baselines.


A study that satisfies the 12 items is review-ready. A study that misses three or more is exposed to material rework risk.



7. Data Provider Ecosystem

Institutional PMA work draws on a tiered data provider ecosystem. Public baselines anchor the analysis. Premium panels calibrate it. Reconciliation between tiers is the methodological discipline.


Public baselines. Census American Community Survey (ACS), 5-year vintage current within the institutional recency window. Census LEHD/LODES 8.3, reference year 2022, released November 19, 2024 (19, 20). Dartmouth Atlas of Health Care, 3,436 HSAs and 306 HRRs (18). HUD income limits and AMI tables. BLS Quarterly Census of Employment and Wages (QCEW) (33).

Demographic segmentation. ArcGIS Tapestry (renamed from Esri Tapestry Segmentation in June 2025; 60 distinct segments organized into 12 LifeMode groups; previous 2024 vintage had 67 segments and 14 LifeMode groups) (21). Claritas PRIZM Premier (68 household segments organized into 14 Social Groups and 11 Lifestage Groups; current vintage 2023 Segment Narratives) (22).

Mobility panels. Placer.ai (mobile-device foot-traffic and origin-destination panel; tens of millions of US devices; panel sample size not publicly disclosed) (30). Advan Research (legacy SafeGraph Patterns mobility data, transferred to Advan at end-2022) (31).

Points of interest inventory. SafeGraph (~5.5M U.S. and 75M+ global points of interest; current focus is POI inventory and brand affiliation; mobility patterns no longer published directly) (32).

Commercial real estate supply. CoStar (U.S., U.K., parts of Canada, and Australia via Domain; office, industrial, retail, multifamily, hospitality, student housing, and land; continuous in-house research updates; portfolio includes STR for hospitality benchmarking, Matterport for 3D digital twins acquired February 2025, Visual Lease for lease accounting acquired November 2024, Ten-X for CRE auctions) (23, 24). Yardi Matrix (top 100+ multifamily markets, approximately 50,000 self-storage facilities tracked; monthly refresh).

Hospitality. STR / CoStar Hospitality (RevPAR, ADR, occupancy benchmarking; STAR report monthly cycle; competitive set rules effective January 1, 2017) (25).

Senior living. NIC MAP Vision (214 CBSAs total, 35,000+ properties, quarterly refresh) (11).

Short-term rental. AirDNA (10M+ Airbnb and Vrbo listings, 120K markets, ~1M partner properties via channel-manager feeds; daily scrape with monthly market aggregation) (26).

The reconciliation discipline. No premium panel is a substitute for the public baseline. Placer.ai and Advan are calibration tools. CoStar and Yardi Matrix are supply inventories. ArcGIS Tapestry and Claritas PRIZM are behavioral overlays. Every premium-panel claim is reconciled back to ACS, LEHD, or the relevant regulatory authority before it is relied upon. A study that quotes Placer.ai without naming the ACS denominator is quoting a number without a context, and the reviewer will catch it.



8. Eight Failure Modes

Common review-stage failures in PMA construction. Each is sufficient to invalidate a feasibility conclusion in institutional peer review.



Failure 1: PMA defined to fit the conclusion. Boundary drawn to produce a capture rate within the desired range rather than from first principles. Detected when the boundary is irregular without barrier justification, or when expanding the PMA produces exactly the qualified demand needed to hit the target capture rate. Fix: document the boundary method before computing capture. Define the PMA first, calculate demand second.

Failure 2: Capture rate exceeds state HFA ceiling without supply-scarcity argument. Capture rate calculated at 15% against a state HFA QAP ceiling of 10–12% (the prevailing LIHTC convention), with no supply-scarcity argument to justify the exception. Fix: either reduce the capture rate to within ceiling or build an explicit supply-scarcity case anchored to local data.

Failure 3: Pipeline supply omitted. Competitive properties in lease-up, under construction, or in state HFA pipeline within the prior two application rounds not enumerated. Mechanical effect: undercount supply, overstate capture. Fix:enumerate pipeline properties with stage (proposed, approved, under construction, lease-up) and projected delivery.

Failure 4: Demographic vintage stale. ACS 5-year data older than the institutional 18-month recency window relative to report date. Segmentation overlays (Tapestry, PRIZM) older than current vintage. Fix: refresh to most current vintage; disclose vintage at first reference.

Failure 5: Deduplication math missing. SMA invoked with aggregate demand counted from both PMA and SMA without deducting PMA in-migration. Double-counts households. Fix: explicit deduplication formula shown; aggregate demand reconciles to total qualified pool.

Failure 6: Trade-area heuristic substituted for origin data. Default 70/30 PMA/SMA split applied where Resident Origin or mobility data is available and would override the heuristic. Fix: use origin data where available; reserve heuristics for data-poor environments and disclose the substitution.

Failure 7: Segment-level penetration applied against wrong denominator. Senior-living penetration ceilings of 10–12% IL, 6–8% AL, 1–2% MC applied against all 75+ households rather than income-qualified 75+ households. Inflates demand by 2–3x. Fix: state the denominator explicitly. Income-qualified 75+ is a narrower set than all 75+; the difference is material.

Failure 8: Single-provider citation without reconciliation. Placer.ai trade-area figure quoted without ACS denominator. Yardi Matrix self-storage saturation quoted without naming source vintage. NIC MAP penetration quoted without disclosing denominator basis. Premium-panel claims uncalibrated to public baselines. Fix: every premium-panel figure cross-referenced to the public baseline that anchors it.



9. The Methodology Triad

A defensible Primary Market Area rests on three pillars: regulatory anchor, methodological discipline, and disclosure.


The regulatory anchor binds the PMA to a published institutional standard. SBA SOP 50 10 8 for SBA-financed projects. USDA 7 CFR Part 5001 for USDA-financed projects. USPAP SR 1-3 for appraisal-adjacent work. NCHMA Model Content Standards Version 3.1 for LIHTC content compliance. State HFA QAP for LIHTC capture math. Appraisal Institute Dictionary of Real Estate Appraisal, 8th Edition, for terminology. Without a named regulatory anchor, the PMA is the consultant's preference rather than the jurisdiction's requirement.


The methodological discipline binds the PMA construction to a defensible method appropriate for the asset class. ICSC conventions for retail. NIC MAP Vision conventions for senior living. State HFA QAP conventions for LIHTC. Census LODES for industrial labor analysis. Dartmouth Atlas for healthcare. Huff, Reilly, and Converse gravity literature where competition is the dominant boundary-shaping force. Without a named method, the PMA is opaque.


The disclosure binds every quantitative claim to a named source with a date of consultation. Demographic vintage. Mobility-panel methodology. Comp-set construction. Capture-rate ceiling source. Pipeline supply enumeration. Without disclosure, the PMA is unauditable.


A feasibility study that satisfies the triad — anchored, disciplined, disclosed — is review-ready. A study that does not is exposed.


The PMA is the geographic answer to a single question: where does demand come from? Every defensible feasibility conclusion begins with a defensible answer to that question, supported by a regulatory anchor, executed through a methodological discipline, and documented through institutional disclosure. The rest of the feasibility study is downstream.


May 12, 2026, by Michal Mohelsky, J.D. Principal of MMCG Invest, LLC, feasibility study consultant serving feasibility studies for assisted living facilities.


Reach out to discuss how our methodology supports your lending decision.




Michal Mohelsky, J.D. | Principal | mmcginvest.com 

Phone: (628) 225-1125




Disclaimer: This report is provided for informational purposes only and does not constitute investment advice. Data presented herein is derived from proprietary MMCG databases and third-party sources believed to be reliable; however, MMCG Invest makes no representation as to the accuracy or completeness of such information. Figures from third-party industry databases have been independently verified and, where appropriate, adjusted to reflect MMCG's proprietary analytical methodology. Past performance is not indicative of future results.



Sources

  1. SBA Information Notice 5000-868665, "Issuance of SOP 50 10 8 with Technical Updates," effective June 1, 2025. sba.gov/document/information-notice-5000-868665.

  2. USDA 7 CFR Part 5001 (OneRD Guaranteed Loan Regulation), current. ecfr.gov/current/title-7/subtitle-B/chapter-L/part-5001. RD Instruction 5001 (07-10-25, PN 648).

  3. Appraisal Standards Board, USPAP 2024 Edition, effective January 1, 2024.

  4. Appraisal Institute, Dictionary of Real Estate Appraisal, 8th Edition (current). appraisalinstitute.org.

  5. NCHMA, Model Content Standards, Version 3.1, updated September 2025. housingonline.com/councils/national-council-housing-market-analysts/model-content-standards/.

  6. ICSC Research with CoStar Realty Information, U.S. Shopping-Center Classification and Characteristics, January 2017. icsc.com/uploads/research/general/US_CENTER_CLASSIFICATION.pdf.

  7. ICSC, Guide to Shopping Center Terms (1995); SCORE publication.

  8. Huff, David L. (1964). "Defining and Estimating a Trading Area." Journal of Marketing, 28(3), 34–38.

  9. Reilly, William J. (1931). The Law of Retail Gravitation. New York: Knickerbocker Press.

  10. Converse, Paul D. (1949). "New Laws of Retail Gravitation." Journal of Marketing, 14(3), 379–384.

  11. NIC MAP Vision, Metro Coverage. nicmap.com/nic-map-metro-coverage/.

  12. NIC MAP Vision senior-housing penetration analysis. info.nic.org; nicmap.com/blog/are-senior-housing-markets-oversupplied-or-overlooked/.

  13. NCHFA 2025 QAP Appendix A, "Market Study Standards and Requirements." nchfa.com/sites/default/files/2024-11/2025QAP-AppendixA-Final.pdf, §II.D.

  14. TDHCA 2025 QAP, 10 TAC Chapter 11, §11.303. tdhca.texas.gov/sites/default/files/multifamily/docs/25-QAP.pdf.

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  16. MHDC 2024 Market Study Guidelines (effective July 15, 2024; revised for 2025 application rounds). mhdc.com/media/fk5o4ki3/market-study-guidelines_2025.pdf.

  17. HUD MAP Guide Chapter 7 (Valuation & Market Analysis), revised March 19, 2021. hud.gov/sites/dfiles/OCHCO/documents/4430GHSGG.pdf.

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  19. U.S. Census Bureau, LEHD/LODES Technical Documentation 8.3. lehd.ces.census.gov/data/lodes/LODES8/.

  20. U.S. Census Bureau press release, November 19, 2024. census.gov/newsroom/press-releases/2024/onthemap-lodes-data.html.

  21. Esri, ArcGIS Tapestry (June 2025 release). esri.com/en-us/arcgis/products/arcgis-data/explore/tapestry-data.

  22. Claritas LLC, PRIZM® Premier Segment Narratives 2023. claritas.com/prizm-premier.

  23. CoStar Group, Inc., Form 10-K for fiscal year 2024 (filed February 20, 2025). investors.costargroup.com.

  24. CoStar Group, Inc., Matterport acquisition press release, February 28, 2025.

  25. STR / CoStar Hospitality, Competitive Set Guidelines (effective January 1, 2017). costar.com/products/str-benchmark/resources/guidelines/competitive-set-guidelines.

  26. AirDNA, methodology documentation. airdna.co/methodology.

  27. Yardi Matrix Self-Storage Report (January 2026), via StorageCafe.com.

  28. Self Storage Association, Industry Data Report 2025. selfstorage.org.

  29. Self-Storage Almanac 2024. MiniCo Insurance / Inside Self-Storage.

  30. Placer.ai methodology and panel disclosures. placer.ai.

  31. Advan Research (formerly SafeGraph Patterns mobility data, assigned end-2022). advanresearch.com.

  32. SafeGraph Places documentation. safegraph.com.

  33. U.S. Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW). bls.gov/cew/.

 
 
 

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