Abstract
We introduce a method that combines Euclidean distancing and OLS techniques to project synthetic capitalization rate indices (‘SCXs’) for metropolitan statistical areas in the US. SCXs are projected independently of market prices, asset specific characteristics and geographic location (ex-ante). In contrast to market cap rates, driven by geographic proximity and market comparables, our new method is driven by economic proximity. We find SCXs provide better forward guidance than market cap rates for commercial real estate (‘CRE’) defaults and CRE values before and during the Covid pandemic. Our method establishes CRE benchmark cap rate indices across property types that explicitly connect CRE valuation at the MSA level to macroeconomic indicators through economic proximity.
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