Statistical Measure and Spatiotemporal Evolution Analysis of Inter-provincial Finance Efficiency of Science and Technology Based on Non-expected SBM Model

Abstract

The report of the 20th Party Congress pointed out that the real economy must be the core of economic development, and the financial sector, as the "backbone" of the real economy, is a key factor in realizing high-quality economic development. Science and technology finance, as a new type of bridge connecting finance and science and technology, on the one hand, accelerates the flow of capital to new technologies, and on the other hand, helps scientific and technological innovations to constantly reach a new level. Although the strength of China's science and technology financial investment has been increasing, the problems of emphasizing investment over performance and unbalanced development of science and technology finance among regions still exist. Therefore, taking the inter-provincial data of the decade 2010-2019 as the research object, based on the input-oriented three-stage SBM-DEA model containing non-expected outputs, we constructed China's S&T financial efficiency evaluation index system to measure the S&T financial efficiency of China's provinces. In order to further empirically test the geographical differentiation of China's S&T financial efficiency, based on the results of the three-stage SBM-DEA, the Dagum Gini coefficient decomposition method is used in combination with Kernel kernel and other statistical methods to reveal the characteristics of the geographical differentiation of China's S&T financial efficiency in China and the trend of its spatial and temporal evolution.