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.

中文翻译：

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综合上限利率指数（1991-Covid 时代）

我们引入了一种结合欧几里德距离和 OLS 技术的方法来预测美国大都市统计区域的综合资本化率指数（“SCX”）。 SCX 的预测与市场价格、资产特定特征和地理位置（事前）无关。与由地理邻近性和市场可比性驱动的市值率相比，我们的新方法是由经济邻近性驱动的。我们发现，对于商业房地产（“CRE”）违约和 CRE 价值而言，SCX 在新冠疫情大流行之前和期间提供了比市值更好的前瞻性指引。我们的方法建立了跨房地产类型的 CRE 基准资本化率指数，通过经济接近度将 MSA 层面的 CRE 估值与宏观经济指标明确联系起来。