TITLE:
Spatial-Temporal Characteristics and Determinants of Innovation Output in China
AUTHORS:
Shujing Guo
KEYWORDS:
Innovation Output, Spatial Autocorrelation, Spatial Spillover Effects, Spatial Dynamic Panel Data
JOURNAL NAME:
Modern Economy,
Vol.10 No.1,
January
10,
2019
ABSTRACT: Based on the Entropy Method, ESDA and spatial panel
data model methods using urban patents database of China’s 285 cities during 2014-2015,
this article explored the spatial pattern and determinants of innovative
output. The results show that: Innovative output shows obvious characteristics
of geographical agglomeration and spatial agglomeration. Most cities had strong
path dependence and lock-in characteristics, and transition didn’t occur. When
the inter-city correlation is considered, human capital and industrial base are the major driving
forces for boosting innovation output. The input of innovation elements will not only promote the improvement of
local innovation ability, but also promote the development of innovation
capability in the neighboring cities.