An Exploratory Canonical Correlation Analysis on Regional Input and Output of Science and Technology

Canonical correlation analysis is a useful multivariate statistical method to assess linear relationships between groups of variables. In this paper, we first build a regional science and technology (S&T) input and output indicators system. Then we take the regional S&T of Jiangsu Province, China, as a typical case study. Second, canonical correlation analysis is used on two group variables, the regional S&T input and output indicators, with the data derived from thirteen cities of Jiangsu Province, and the sample period is from 1996 to 2005. Furthermore, we analyze the S&T input and output relationship by extracting two pairs of canonical variables, and reveal the internal links of dominant indicators between the two group variables. The results would give us better understanding of S&T input and output relationship. Finally, we discussed the S&T policy implications for Jiangsu Province based on the quantitative results.