Abstract
Purpose This paper aims to investigate the effect of the COVID-19 pandemic market shock on house pricing, time-on-market (TOM) and probability-of-sale functions using local multiple listing service data from Richmond, Virginia, USA. Design/methodology/approach The empirical analyses use a two-stage residual inclusion model to simultaneously address endogeneity and nonlinearity in modeling sales price and TOM, and a Heckman two-stage procedure to account for sample selection bias in estimating the probability-of-sale. Findings The pandemic shock not only directly impacted average home prices, TOM and probability-of-sale, but it also caused the coefficients of some of the factors that influence these metrics to change while others were stable to the exogenous shock of the pandemic. The authors find that coefficients in the hedonic pricing, TOM and probability-of-sale models did not shift instantaneously; instead, the impact evolved over several months at the beginning of the pandemic until stabilization. Originality/value The results should be of interest to buyers and sellers of residential properties, agents specializing in residential properties and researchers looking to better capture the impact of exogenous events on housing prices and buyer preferences.
