Top Data Sources for Real Estate Private Equity Market Analysis

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Build a Fast, Auditable REPE Data Stack for 2025

Real estate private equity is capital invested in income-producing property with hands-on management to grow cash flow and value. Market analysis means turning data on rents, occupancy, cap rates, supply, and financing into forecasts you can underwrite and defend. A data source is any dataset with known coverage, timing, and method that feeds those forecasts.

This guide shows how to choose, combine, and govern the right datasets so your underwriting is faster, more precise, and ready for investment committee. The payoff is simple: if your inputs are disciplined, you can move first when pricing dislocates and still pass audits later.

Choose sources you can defend in IC

Underwriting lives or dies on the quality and timing of your inputs. Useful sources share a few traits: clear property and geography definitions, consistent history, frequent updates, published methods, and licenses that let you use outputs in models and LP materials. Favor datasets you can reproduce with query IDs and versions; if an auditor cannot rerun it, assume an IC chair will ask why.

Judge each source on five axes and document the decision.

  • Relevance and coverage: Confirm property type taxonomy, geographic granularity, and historical depth match your thesis.
  • Latency and frequency: Monthly or quarterly beats annual for fundamentals; daily matters for rates and public markets.
  • Method and bias: Distinguish asking vs. effective rents and realized vs. appraised values; check survivorship and withholding rules.
  • Auditability: Require footnotes, query IDs, version history, and API support for reproducibility.
  • Legal use: Verify license scope, redistribution rights, model rights, and PII handling to avoid compliance surprises.

Standardize macro baselines before you model

Macro assumptions set boundaries for rent growth, exit pricing, and debt sizing. Do not mix series with different seasonal adjustments or geographies; that muddles comparability.

  • Inflation and wages: Use BLS CPI and Employment Cost Index for inflation and wage pressure. As of November 2024, CPI year-over-year was 3.1%. If nominal yields hold, higher real rates pressure cap rates and valuation near term.
  • Employment and population: BLS payrolls and Census ACS tie to tenant demand and household formation. Use county and state crosswalks to align ACS with your submarkets for faster modeling.
  • Rates and credit: Pull the U.S. Treasury curve and SOFR daily for discount rates and loan pricing. For credit availability, triangulate Mortgage Bankers Association originations with bank disclosures and the FDIC Quarterly Banking Profile for execution certainty.

Track transactions and valuations separately

Transaction data links sentiment to executable pricing. Keep appraisal-based and transaction-based measures separate in your analysis and workbook.

  • MSCI Real Assets: Broad deal coverage with price, cap rate, buyer, seller, and financing when available. Monthly US Capital Trends helps with cross-border flows and distressed activity. Watch reporting timing in smaller markets and model-driven fields when trading thins.
  • Green Street CPPI: A transaction-based, constant-quality index that clarifies sector-level price movements. As of November 2024, it showed double-digit declines from 2022 peaks across most sectors – useful for re-marking portfolios and scenarios. Pair it with local comps for asset-level underwriting.
  • Public REIT signals: NAREIT and S&P Global Market Intelligence provide implied cap rates, NAV discounts, and equity windows. Public markets often move first in dislocations; use these to stress exits and equity cost of capital.
  • Broker cap rate surveys: CBRE and JLL publish biannual ranges by market and property type. Treat them as directional and cross-check with closed deals and REIT implied yields.

Underwrite the operating line items that drive NOI

Underwrite effective rents, not rack rates. Lease behavior drives cash flow.

Multifamily fundamentals

  • Yardi Matrix and RealPage: Both report asking and effective rents, occupancy, lease trade-outs, and renewal rates at property and submarket levels. Yardi’s rent rolls and debt recording often give sharper asset-level context. RealPage offers deep resident retention and concessions analytics. Panels and client mixes differ, so reconcile trends before forecasting absorption.
  • Freddie Mac and Fannie Mae research: Quarterly rent and vacancy outlooks tie into debt sizing and takeout assumptions and anchor the bridge from macro to micro.
  • Zillow and Apartment List: Faster signals tilt toward single-family and smaller units. Use for nowcasting direction, not as a sole underwriting input.

Office, industrial, and retail

  • CoStar: Broad inventory, availabilities, asking rents, absorption, and pipeline, with highest quality in major metros. Review effective rent methodologies and tenant renewals; track vintage changes and reclassifications.
  • CBRE Econometric Advisors and JLL Research: Demand, deliveries, and vacancy forecasts informed by broker pipelines and tenant rep insights. Use as base cases and validate against BLS employment in sector-relevant industries.
  • CompStak: Lease comps with rents, tenant improvements, and free rent. Best in office-heavy markets; use to test concessions and true net effective rent on re-tenanting.

Hospitality and short-term rentals

  • STR: Hotel occupancy, ADR, and RevPAR by chain scale and market. Essential for underwriting rate elasticity and shoulder seasons.
  • AirDNA: Short-term rental supply, occupancy, and rates for vacation markets. Helpful for leisure-driven markets and SFR-to-STR pivots. Reconcile with STR to gauge substitution effects.

Specialized property types

  • Self-storage: Yardi Matrix and Radius+ provide rents, pipeline, and street-rate trends. Micro trade areas matter, so use drive-time polygons, not zip codes.
  • Data centers and life sciences: CBRE, JLL, and niche trackers report take-up, power constraints, and lab vacancy. Validate against utility interconnection queues and permitting to plan capex timing.
  • Student and seniors housing: RealPage Student and NIC MAP Vision provide occupancy and pre-lease rates. Stress against enrollment and demographic baselines to control demand risk.

Measure supply and replacement cost

Supply surprises derail theses. Combine public permits with private project trackers and back into replacement cost with a consistent method.

  • Census permits and construction spend: Monthly permits and put-in-place spend give an early read on new supply. Use permit valuations and a simple cost approach to estimate replacement cost for capex planning.
  • Dodge Construction Network: Project-level starts, bids, schedules, and contractors. Helps verify pipeline and delivery timing.
  • Zonda: Single-family and lot inventory, absorption, and prices for SFR and build-to-rent strategy work.
  • CoStar pipeline: Cross-check inventories and lease-up schedules by submarket to avoid double-counting across sources.

Map debt markets and credit risk

Debt cost and availability now swing outcomes more than they did in 2015 to 2019. Build a consistent view across securitized, agency, and bank lenders.

  • Trepp: CMBS, SASB, and CRE CLO loan-level data, watchlists, DSCR, and maturity schedules. Delinquency trends surface distress early. Use remittance data for current NOI, not just issuance underwrites. For structure context, see this primer on CMBS securitization.
  • Moody’s Analytics and KBRA: Credit metrics, loan-tape analytics, and rating actions. KBRA surveillance often flags property-level risks and capex needs ahead of headlines.
  • FDIC Quarterly Banking Profile: Bank-level CRE exposures, criticized assets, and charge-offs. Separate multifamily from nonfarm nonresidential and map regional bank exposure in target MSAs.
  • Freddie Mac K-Deals and Fannie Mae DUS: Loan tapes, performance, and prepayment for agency multifamily. Agency shifts spill into private term sheets for similar collateral.

Sharpen selection with alternative and geospatial data

These datasets improve asset selection, tenant diligence, and micro-location calls. Handle licenses and privacy carefully.

  • Mobility data: Placer.ai, SafeGraph, and Veraset show visits, dwell time, and trade area share by brand and daypart. Validate against parking and POS data and known seasonal patterns.
  • Climate and hazard: First Street Foundation and FEMA map flood, fire, and heat risk. Integrate into reserves, insurance forecasts, and downtime assumptions. Insurer pullback can hit NOI harder than rent growth helps.
  • Satellite and imagery: Orbital Insight and Kayrros help track construction progress, parking lot counts, and supply chain disruptions. Use for targeted confirmation given costs and noise.

Use public markets to time entries and exits

  • NAREIT and FTSE Nareit: Daily sector performance and implied cap rate moves for REITs. Issuance windows correlate with private exit liquidity. For fundamentals context, review FFO as a valuation metric.
  • NCREIF: NPI and ODCE provide appraisal-based returns, leverage, and sector weights. Use for benchmarking and investor reporting, not transaction timing.
  • Preqin and PitchBook: Fundraising volumes, dry powder, and time-to-close by strategy. Calibrate competition and terms; adjust hurdle rates when fundraising slows or LP concentration rises.
  • MSCI benchmarks: Global capital flows and performance help cross-border allocators normalize expectations.

Recognize tax, legal, and regulatory constraints inside the data

  • Zoning and land use: Portals and aggregators supply overlays, FAR, height, and use rules. Set alerts for text changes that affect density or parking minimums.
  • Property tax and assessments: County assessor data and state equalization rates flow straight to NOI. CoreLogic or ATTOM can normalize parcel IDs and assessment history; align with appeal timelines.
  • Beneficial ownership and KYC: Corporate Transparency Act reporting affects JV structures and timing. Track entity ownership changes and residency for withholding and treaty claims.

Assemble a stack by strategy

Core and core-plus

  • Current state: CoStar for occupancy and rent comps; validate with Yardi Matrix for multifamily and STR for hotels.
  • Mark risk: Price check with MSCI comps and Green Street CPPI for sector repricing direction.
  • Discipline: Forecast with CBRE EA or JLL and constrain with BLS employment growth in relevant industries.
  • Optics: Benchmark to NCREIF ODCE and NPI for LP reporting.

Value-add and opportunistic

  • Cash flow realism: Add CompStak for effective rent, tenant improvements, and free rent on reletting.
  • Execution risk: Track supply via Census permits and Dodge starts; align with your construction or repositioning timeline.
  • Sourcing: Monitor distress via Trepp watchlists and special servicer transfers; build a pipeline from maturing CMBS and CLO cohorts by MSA and property type.
  • Merchandising risk: For retail and mixed-use, use Placer.ai to quantify trade-area capture before setting tenant mix.

Credit strategies and rescue capital

  • Timing: Use Trepp and KBRA to size refinancing walls and DSCR shortfalls; map to loan terms to flag extension risk.
  • Workout path: Overlay FDIC bank exposure to find lender cohorts likely to de-risk; segment community banks and money centers.
  • Loss modeling: Agency multifamily tapes provide a comparison set for underwriting stringency and loss history; anchor LGD where collateral matches.
  • Deal timing: Monitor the SOFR term structure daily; link to repricing dates and cap agreements to map borrower pain points.

SFR and build-to-rent

  • Absorption: Combine Zonda for new-home supply with Zillow rent indices for neighborhood pricing.
  • Speed: Use county deed and recorder feeds via CoreLogic or ATTOM for acquisition ID and portfolio roll-up.
  • Compliance: Mobility data can validate commute and amenity patterns; follow privacy and license limits.

Quick math checks that prevent wishful thinking

  • Cap rate sensitivity: Moving from a 5.0% to a 6.5% exit cap cuts value by roughly 23% if NOI is unchanged. A 150 bp move at low caps hits harder due to the inverse price-cap relationship.
  • Effective vs. asking rent: If asking is $40 NNN, concessions include two months free on a five-year term, and TI is $60 per square foot amortized at 8%, effective rent lands around $34 to $35.

Data mechanics that reduce errors

  • Normalize taxonomy: Align property types, class A/B/C, and construction status across sources; keep a mapping table with version control.
  • Anchor to a master calendar: Tag each record with as-of and through dates; freeze vintages for IC so restatements do not rewrite history.
  • Record lineage: Store query IDs, dataset versions, and transformation code hashes. Reproducibility shortens due diligence questionnaires.
  • Prioritize effective measures: Favor effective rent, leased occupancy, and realized cap rates over marketed figures.
  • Build variance checks: If two rent sources differ by more than 150 to 200 bps year-over-year for the same submarket, stop and reconcile.

Common pitfalls and the kill tests to apply

  • Asking vs. effective confusion: Kill test: does the source disclose concessions and TI methods? If not, use for trend only.
  • Appraisal survivorship bias: Kill test: are entry and exit rules and backfill practices published?
  • Sample instability: Kill test: do restatements frequently exceed 50 bps without documentation?
  • Latency mismatch: Kill test: is update cadence aligned with IC timing?
  • Inconsistent geographies: Kill test: have you harmonized geographies with a crosswalk and tested aggregation?
  • Single-source overfit: Kill test: do you have at least two independent measures for variables that move value?
  • License constraints: Kill test: can you pass through derived metrics and images to LPs and lenders under contract, and is there a redaction plan?

Implementation plan with clear owners

  • Weeks 0 to 2 – Requirements and procurement: Define assets, geographies, and deadlines. Legal reviews licenses for model and redistribution rights; security reviews PII handling.
  • Weeks 2 to 6 – Integration: Engineering builds API or SFTP ingestion. Data management sets taxonomy mapping and version control. Analytics validates against public benchmarks.
  • Weeks 6 to 8 – Pilot: Apply the stack to one live and one historical deal. Investment and asset management review variances vs. prior models; adjust source weights and defaults.
  • Weeks 8 to 12 – IC-ready release: Lock datasets to a vintage. Publish a data dictionary with sources, as-of dates, and known biases. Capture query parameters for every IC exhibit.
  • Ongoing – License and quality review: Replace weak datasets, add kill tests when new biases surface, and track privacy and beneficial ownership updates that could change access or sharing.

Operationalize governance for speed and trust

  • Set a source of truth per variable: Example: rents – Yardi Matrix primary, RealPage cross-check; occupancy – CoStar primary, broker research cross-check.
  • Maintain a data issues log: Record anomalies, fixes, dates, and owners; tie material fixes to IC memos when they changed a conclusion.
  • Use scenario bands: When sources diverge, present low, base, and high cases with query IDs and rationale.
  • Fresh angle – the evidence binder: For every value-driving input, maintain a one-page PDF with chart, query ID, and license note that can be dropped into LP decks and audits in seconds.

Cadence: what to track when

  • Weekly: REIT performance and implied cap rates; U.S. Treasury and SOFR curves; Trepp delinquencies and special servicer transfers in target MSAs; active broker mandates coloring leasing.
  • Monthly: Yardi or RealPage and CoStar rents and occupancy; Census permits; STR hotel metrics; mobility footfall; Green Street CPPI.
  • Quarterly: MSCI transaction trends; NCREIF indices; FDIC bank exposure; Preqin fundraising and dry powder; agency multifamily performance.

Final IC checks before you hit send

  • Clarity: Every datapoint shows value, unit, as-of date, and source, or is labeled directional with reason.
  • Credibility: Numbers reconcile across sources within a documented tolerance; if not, present range and cause.
  • Compliance: Third-party charts and stats meet license and attribution. Remove anything that cannot be shared.
  • Risk control: Stress cases draw from independent sources for rent, exit cap, and debt cost. One vendor vintage should not drive all three.

Closeout and retention

Archive datasets, queries, versions, user access, and full audit logs; hash archives; apply retention schedules; require vendor deletion with a destruction certificate; and remember that legal holds override deletion. As a resilience add-on, pre-plan substitute sources and a backfill procedure so a vendor outage cannot stall underwriting during a live deal.

Closing Thoughts

Underwriting in 2025 rewards teams that build a data stack that is fast, specific, and auditable. Start with public baselines, add sector-specific private sources, and layer targeted alternative data where it truly sharpens the view. Treat data as an asset with procurement, QA, and an audit trail, and your investment process becomes quicker and more defensible when markets move.

Further reading: If you are new to real estate private equity, see this overview. To contrast private vehicles with REITs, compare structure and liquidity. For strategy nuances across core, value-add, and opportunistic, study risk-return bands. If you want to speed up modeling, review the best financial modeling courses. Finally, if you are evaluating direct lending alongside equity, align data needs to the credit box.

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