CoStar: commercial real estate transactions (licensed)

Licensed: not exercised here

CoStar is a licensed commercial dataset (CoStar Group), so it carries no provenance badge: the access path below was not run in this session (no CoStar credentials were available). The page documents the access route and the gotchas; treat it as unverified until someone exercises it through a licensed account. This is the honest grade under the institute’s Verified discipline.

CoStar is a commercial real estate database published by CoStar Group. It records property-level data on completed sales, active and historical listings, leases, assessments, and physical and location characteristics across US markets. It is a common source in commercial real estate research: used in, for example Nozawa & Tsoy for completed CRE sales across 15 US cities, 1998Q1 to 2022Q3, including sale price, assessment value, and property characteristics, with days-to-sell as a liquidity proxy.

• Cost: licensed, subscription (broker/investor product; academic access via a data agreement or negotiated extract). No free tier.
• Vendor: CoStar Group.
• Coverage: US commercial properties (office, retail, industrial, multifamily) by metro and submarket, with sale transactions, listing dates, and property attributes; depth varies by market and era.

Access (when licensed)

• Directly from CoStar. The common path is the CoStar platform, with exports or a negotiated data extract arranged through CoStar Group. There is no standard WRDS path for CoStar.
• Credentials and a valid license are required. Keep them in .env, never hard-coded.

Gotchas (the ones that bite pipelines)

These are the failure modes to expect; they are documented, not verified here.

• Coverage is a selected sample, not a census. CoStar records marketed or observed properties and skews toward larger metros and institutional-grade assets. Absence of a property in the data is not evidence that the property does not exist or that no transaction occurred.
• Listing and delisting dates can be noisy or missing. Any days-to-sell measure depends on these dates, which are entered and maintained by brokers. Verify the completeness of listing-date fields for your markets before constructing liquidity measures.
• Prices mix multiple sources. The price field can reflect a reported sale price, a broker estimate, or an assessment value. Keep the price type explicit and consistent; do not blend types without flagging them.
• The live platform is continuously updated and overwritten. Reproducing a historical pull requires a dated extract: a fresh pull from the platform will not match an older one. Archive the extract date and its scope.
• Property and submarket definitions are CoStar-specific and not stable across vintages. The CoStar property identifier and submarket boundaries can shift between platform versions; pin the vintage before linking across files or time periods.
• Duplicate and revised listings need de-duplication. A single property can appear under multiple listing records (original, revised, relisted); decide on a de-duplication rule before constructing the analysis sample and document it.

Citation

Cite the product and vendor, stating the extract date and vintage, the markets and time period covered, the price field used, and how listing and delisting dates were cleaned, e.g.: CoStar commercial real estate data, CoStar Group, extract dated YYYY-MM-DD; markets: [list]; period: [start] to [end]; price field: [field name]; listing-date cleaning: [description].