An empirical study of China＇s regional R＆D knowledge spillovers based on GWR

The present paper employs technique of geographical weighted regression （GWR） to make an empirical study of China＇s R＆D knowledge spillovers at city level. Conventional regression analysis can only produce ＂average＂ and ＂global＂ parameter estimates rather than ＂local＂ parameter estimates which vary over space in some spatial systems. Geographically weighted regression （GWR）, on the other hand, is a simple but useful new technique for the analysis of spatial non-stationarity. Results show that there is a significant difference between OLS and GWR in estimating the parameters of R＆D knowledge production, and that the relationships between level of regional innovation activities and various factors show considerable spatial variability.