Total factor productivity and the factors of green industry in Shanxi Province, China

Abstract

Based on industrial panel data from 11 prefecture‐level cities in Shanxi Province from 2008 to 2016, two kinds of total factor productivity (TFP) are measured: With and without the consideration of environmental factors. The specific decomposition of TFP under these two conditions is then discussed. Finally, the factors of TFP are studied in a green industry context. The results indicate the following: (a) The TFP's annual growth rate considering environmental conditions is higher than that without such consideration; (b) if environmental factors are neglected, TFP improvements primarily depend on technological progress; (c) when considering environmental factors, both technological progress and improved technological efficiency promote the growth of green TFP (GTFP), but this still primarily depends on substantial technological progress, with an annual average growth rate that reaches 10.2%; and (d) among factors, the economic development level, degree of openness, and urbanization positively correlate with the GTFP, while the industrial structure and degree of informatization significantly and negatively correlate with GTFP.

Towards sustainable development: How does technological innovation drive the increase in green total factor productivity?

“…And, urbanization is positive but statistically insignificant to GTFP. The results are consistent with that of Song and Li (2020) for China.…”

“…However, numerous studies expose the negative impact of urbanization. Song and Li (2020) conclude that urbanization is not significantly correlated with GTFP. Liu, Huang, and Chen (2019) assert that the increasing population density negatively affects green development.…”

“…Nonetheless, Song and Li (2020) concede that an industrial structure inhibits and negatively correlates with GTFP. Subsequently, Wang, Li, and Fang (2018) estimate the direction of and bias against technological progress under environmental constraints, based on data of Chinese provinces from 2004–2015.…”

Spatial-Temporal Distribution Characteristics and Driving Mechanism of Green Total Factor Productivity in China’s Logistics Industry

“…The combination of the EBM model with the GML index is adopted to calculate the GTFP of the logistics industry. Therefore, the expression formulae of the GML index are as follows: (7) ...where g = (-x, y, -b), and it represents that under the given technical conditions, the desirable output y increases proportionally while the undesirable output b and input x shrink proportionally. Besides, β represents the maximum possible value of increase and decrease.…”

“…Wang et al [5] applied a model combining DEA and Shephard distance function, namely production-theoretical decomposition analysis (PDA), to explore the influencing factors of industrial carbon emission intensity changes. In recent years, with the increasingly important role of environmental issues in sustainable development, when applying the TFP to evaluate the efficiency of economic growth, we must consider not only traditional inputs such as capital and labor, but also the effects of resource consumption and environmental pollution on economic growth [6,7]. Otherwise, it may overestimate the true performance of economic growth [8].…”