Data for factors influencing renewable energy technology innovation from a spatial perspective

This
study examines a balanced panel dataset from 29 provinces in China from a
series of statistical yearbooks (2007–2018). Considering the availability and representativeness of the data, this
study focuses on 29 provinces, excluding Hong Kong, Macao, Taiwan, Tibet, and Chongqing for 2006–2017.Using
the International Patent Classification (IPC) code and
combining this with the relevant literature, this study obtained the number of invention
patents granted for different renewable energy sources from the website of the State Intellectual Property Office (SIPO), as well as
the index value for RETI by summation.The
R&D intensity of the enterprises, public institutions, and universities in
each province was obtained by calculating the proportion of the internal
R&D expenditure divided by the regional GDP. The data for internal R&D
expenditure and regional GDP were obtained from the China Science and
Technology Statistical Yearbook and the China Statistical Yearbook. The
provincial human capital was obtained from the human capital website of Renmin
University, which represents the actual total amount of provincial human
capital. The marketing degree indicator for each province was obtained from the
China Provincial Marketing degree Indicator Report (2018). The installed
capacity of the renewable energy in each province was obtained from the China
Electric Power Yearbook.