ABSTRACT
Most countries implemented restrictions on mobility to prevent the spread of COVID-19. As a result, changes in human mobility have affected commercial real estate markets. This study reveals how local factors have been correlated with mobility reductions and evaluates the impact of changes in human mobility on commercial real estate cash flows in Canada. We first use a machine learning model, the least absolute shrinkage and selection operator (LASSO) to determine the best predictors of human mobility change. Then we analyze the impact of mobility reduction on the operational cash flows of Canadian Real Estate Investment Trusts (REITs). Our findings demonstrate that properties in locations with more significant mobility reductions were associated with lower real estate returns. We provide a tool that quantifies the exposure of REITs to such human mobility shocks.