Impact of biased technological progress on the total factor productivity of China's manufacturing industry: The driver of sustainable economic growth

Sustainable economic growth relies on an increase in total factor productivity (TFP). To upgrade the core competitiveness and support the sustainable growth and high-quality development of China's economy, ascending TFP in China's manufacturing industry counts. This study analysed the impact of biased technological progress on TFP, which was estimated by using the relevant data of 27 subsectors of China's manufacturing industry from 1980 to 2019. The results revealed that from the early industrialisation period (1980-2000) to the mid-industrialisation period (2001-2012) and then to the middle and late industrialisation period (2013-2019), the mean value of TFP in China's manufacturing industry grew from 0.291 to 0.394 and then to 0.555, embodying a continuously upwards advancing tendency. Technological progress was capital biased from 1981 to 2011 and labour biased during the rest of the sample period. In addition, its direction was heterogeneous among various industries. To some extent, the growth of TFP has been hindered by biased technological progress and factor allocation. The per unit increase in them has led to 1.495 and 1.017 unit decreases in the TFP. Upon examining the factor efficiency and the factor structure, we found that the estimated coefficients of biased technological progress dropped to-1.516 and-1.719, preventing TFP from growing to a greater extent. Consequently, there is room for their optimisation in China's manufacturing industry.

Automated summary

Sustainable economic growth in China relies on increasing total factor productivity (TFP) in the manufacturing industry. This study analyzed the impact of biased technological progress on TFP using data from 27 subsectors of China's manufacturing industry from 1980 to 2019. The results showed that TFP in China's manufacturing industry has consistently increased over time, but biased technological progress and factor allocation have hindered its growth. Optimizing factor efficiency and structure can address this issue and further improve TFP in the manufacturing industry.