The study quantifies liquidity impacts measured by the Demand-Supply Gap in terms of asset pricing implications for US private commercial real estate markets of the COVID-19 crisis. So far (using data up to April 2020), New York is hardest hit among the eight metros examined, with a predicted...

In this paper we propose a new methodology for the estimation of fundamental property-level investment real estate time series performance and operating data using real estate investment trust (REIT) data. The method-ology is particularly useful to develop publicly accessible operating...

In this paper we combine a random effects model with different machine learning algorithms via an iterative process when predicting commercial real estate asset values. Using both random effects and machine learning allows us to combine the strengths of both approaches. The random effects will...

We investigate how local information externalities affect investments in tangible durable assets via real options. Using geocoded transaction-level data on US commercial properties from 2000 to 2018, we find that investors have a higher propensity to invest in a property for immediate...

Combining granular data on temperatures across the continental US with micro-level com-mercial real estate (CRE) data from 1980 to 2020, we study the impact of exposure to extreme temperature shocks on investment performance of CRE at the individual asset level. We find that exposure to extreme...

Concerns over rising office vacancy rates and falling office building property values in many urban areas have increased the pressure on cities and developers to consider converting underused office space to residential use. To aid in current and future conversations surrounding the feasibility...