Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This article investigates the spatial interdependence within China's real estate industry, a sector assuming increasing importance in the national economy. The Global Vector Autoregressive (GVAR) model allows us to explicitly address the presence of spatial linkages, including spillover and backwash effects, without a stringent requirement on data. Applying the model to monthly Chinese provincial data for the first time we highlight clear advantages in forecasting and steady-state value prediction. We also demonstrate through the contemporaneous correlation coefficients a growing divide between the previously highly industrialized north and the rest of China. The insights provided by our empirical study have clear value to a wide range of audiences, including researchers, policy makers, and business investors.