Economic and demographic indicators

Alongside the CRE evidence, EQUIRE carries a metro-level indicator layer: 205 metrics across 17 categories, covering 925 US metros. Sixteen federal agencies and research publishers stand behind them. These answer the questions underwriting asks about a market rather than about a building: is employment growing, who is moving in, what is being permitted, how exposed is the metro to natural hazards.

Categories and publishers

Every metric carries its own unit, polarity, vintage, and definition. Ask the assistant for getMetricDefinitions to read the live definition of any one of them, rather than relying on a table that can drift.

National macro context

Separately from the metro layer, EQUIRE carries seven national series sourced from FRED, each on its own publication cadence and running from 2016: the 2-year and 10-year Treasury daily, the 30-year mortgage rate weekly, CPI, the federal funds rate and total nonfarm payrolls monthly, and real GDP quarterly. EQUIRE reads them from the data producer's mirror of those series rather than calling FRED at request time. These supply rate context and the spread comparisons on the Capital markets tab of Market research.

Metrics that are computed, not observed

Fourteen of the 205 are derived by the data producer from other metrics in the same registry rather than observed: seven sector and composite scores, six paired confidence fields, and one composite rank. They are useful for ranking and triage. They are not observations, and two properties of them are commonly misread.

Confidence fields measure coverage, not strength

Each sector score ships a paired _confidence value. That value is the share of the recipe's weighted inputs that actually had data. A low confidence means the score was computed from a partial recipe. It does not mean the market is weak.

The multifamily opportunity score substitutes a neutral value

mf_opportunity blends two sub-scores, 70% demand and 30% supply tightness. When a sub-score has too little data to compute, it is replaced with 50, a neutral value, rather than dropped. A score built on one real sub-score therefore still reads mid-range and looks unremarkable. Its paired confidence field is the only signal that this happened. Read the two together or not at all.

One name that means something different here

vacancy_rate in this layer is residential vacancy from the Census American Community Survey. It is a housing-stock measure covering homes, not a commercial market vacancy rate for office, industrial, or retail space.

No source in EQUIRE's own market pipeline publishes a commercial market vacancy rate. A broker market report you link to a deal can carry one, and it stays labelled by that report's own source, grain, and period; it is context rather than a figure underwriting is graded against. The reasons are on Coverage, freshness, and limits.

Vintages vary by series

These metrics are not published on one calendar, and EQUIRE does not force them onto one. Monthly employment series run within a couple of months of current. Census ACS series are 5-year rolling estimates. Business dynamics and migration series lag by two to three years, because that is when the agency publishes them.

Each metric carries its own observation date. When Market research compares a figure against your underwriting, it shows that date rather than the date the comparison ran.

Where this layer appears

• Deal chat, Portfolio chat, and Prospecting chat read it through getMarketData, compareMarkets, searchMarkets, getMarketTrends, and getNationalMacro when Market data is enabled in chat settings.
• Market research reads it for the Market tab peer comparison, the employment path, the Location tab hazard exposure, and the inflation check behind expense growth.
• Valuation does not read it. Assumption changes sourced from market evidence arrive as proposals, never as applied values.