Housing price, districts, and transportation infrastructure: a study of price spillover in Shanghai by GVAR method
Date
2017
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
University of Delaware
Abstract
This dissertation provides an empirical study of housing price spillover in metropolitans Shanghai. In this study, Shanghai is divided into nineteen districts based on geographic locations and official administrative districts. Given the close connection among the districts, the spillovers in housing prices across districts are expected to be particularly strong. This study focuses on the spillover of housing prices at the district level, in particular, how a housing price shock in one district spreads over to other districts. A global vector autoregressive (GVAR) model is estimated with district-specific variables, weighted foreign variables, and common variables. The novelty of this study lies in the construction of a time-varying weight matrix used in the GVAR model. Previous GVAR studies on housing prices have used physical distance or neighbor indicators to construct the weight matrix, which is guaranteed to be a constant. This study instead uses commute time to construct the weight matrix, which is time-varying since several new lines of public transportation have been constructed during the sample period. In addition, using simulation study and counter-factual analysis, this study also estimates to what extent the newly-constructed public transportation affects the spillover effects in the Shanghai housing markets as well as the effect of money supply on housing prices. The conclusions from this dissertation could have significant policy implications for urban planning and public finance.
Description
Keywords
Social sciences, China, GVAR, Housing price, Price spillover, Transportation