China’s Industrial TFPs at the Prefectural Level and the Law of Their Spatial–Temporal Evolution

Calculating China’s industrial total factor productivity (TFP) at the prefectural level comprehensively and accurately is not only an inevitable requirement for China’s industrialization to enter the new development stage of “improving quality and efficiency”, but also a practical need for TFP improvement at the industrial level. Based on the improved Solow residual method with the general nesting spatial model embedded, this paper comprehensively calculated the industrial TFPs of 280 prefectural cities in China from 2003 to 2019, and undertook a detailed analysis of the spatiotemporal evolution law of the calculation results through Dagum’s Gini coefficient and kernel density estimation. Three main conclusions have been drawn in this paper. First, there is an apparent spatial difference among the industrial TFPs of the prefectural cities in China. It is the poorest and has an evident declining trend in northeast China, and best in eastern China, while the development of central and western China is between east and northeast China. Second, the spatial difference level of industrial TFPs of the prefectural cities in China shows a general development trend of firstly falling and then rising. Comparatively speaking, the contribution of intra-group differences is low, while the contribution of inter-group and the intensity of trans-variation are high. Third, the spatiotemporal evolution of China’s industrial TFPs at the prefectural level has the following characteristics: the overall distribution curve moves firstly towards the right and then left, the kernel density at the peak point continuously declines, the distribution ranges are firstly widening and then narrowing, and the tails of the distribution curve are constantly extending. Meanwhile, the distribution figures of the kernel density estimation in different regions show apparent heterogeneity.