The digital effects on structural change: data as a new driver of China’s economic growth

This paper investigates how the data factor of production (DFP) reshapes economic structure and productivity dynamics under environmental constraints. We propose a directional input distance function model within a meta-frontier framework to characterize DFP-embedded production technology. The model highlights the asymmetric relationship between DFPs and traditional inputs, specifying that while DFPs enhance productivity, they are not essential for generating positive output. Applying this parameterized model to a panel dataset of 285 Chinese cities from 2013 to 2022, we find a significant acceleration in productivity after the central government’s formal institutionalization of data as a factor of production. The direct contribution of DFPs accounts for approximately 40 % of this growth. A regional heterogeneity analysis reveals that while all regions share this common growth trend, their underlying drivers differ: the eastern region relies on technological innovation, whereas the central and western regions depend on efficiency catch-up. In addition, our estimates of substitution elasticities reveal the heterogeneous role of DFPs, which are found to be dependent on human capital (complementarity) while serving as a weak substitute for capital and energy. These findings underscore the critical role of digital infrastructure and targeted policies in facilitating the green economic transformation.