Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 248-260 |
| Number of pages | 13 |
| Journal | Economic Modelling |
| Volume | 67 |
| DOIs | |
| Publication status | Published - Dec 2017 |
Keywords
- Chinese provincial linkages
- Forecasting
- Global VAR
- Real estate investment
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