Green innovation marks the high-tech
industries under green development background, which needs governmental
supports. Disagreement exists in the research of the relation between
governmental supports and green innovative efficient, and insufficient studies
on regional differences and mechanism. This paper, based on China’s provincial
panel data of high-tech industries, uses DEA model to measure their 2009 to
2020 green innovative efficiencies of China’s 28 provinces, autonomous regions
and municipalities, and applies the Global Moran’s Index to check the spatial
autocorrelation of the green innovative efficiency of high-tech industries.
Mixed fixed effects spatial lag model is employed to analyze the impacts of
governmental supports on high-tech’s green innovative efficiencies, and the
robustness test is carried out using the method of variable replacement. The
regression analysis on the impacts of government supports on green innovation
efficiency of high-tech industries has been carried out in the eastern, central
and western regions of China to assess internal mechanism of governmental
supports. China’s average values of green innovative efficiency of high-tech
industries has risen to 0.611 from 0.511 during 2009 to 2020, with eastern
higher the national average, and central and western lower. According to the
Moran index test, the green innovation efficiency of China’s high-tech industry
shows strong positive spatial correlation under the spatial weight matrix from
2009 to 2020. Governmental supports show an outstanding inverted U-shaped
relation with green innovative efficiency of high-tech industries, which is
positively contributed by environmental regulations, economic performance and
foreign direct investment. Impacts of governmental supports vary with eastern,
central and western. Governmental supports cast a directive role on green
innovative efficiency, displaying an obvious inverted U-shaped relation with
enterprises’ research & development investments. This paper presents
suggestions that governments make appropriate subsidy range according to high-tech’s
actual situation, with supportive policies varying with regions, industries and
eco-environments.