关键词: 数字经济, 新质生产力, 资源错配, 产出变动分解, 要素扭曲效应

Abstract: This study extends the traditional economic growth accounting by incorporating data elements, thereby developing a theoretical framework that examines how distortions in three factor inputs (capital, labor, and data) affect total output. Utilizing data from Chinese listed companies from 2012 to 2022, we estimate digital new quality productivity levels and resource misallocation degrees across three key sectors: scientific and technological research-related industries, core digital economy industries, and selected high-end manufacturing industries. Our analysis decomposes the contributions to output changes and measures the distortionary effects of these three factors. The findings reveal four key insights. First, digital new quality productivity among listed companies exhibited a fluctuating upward trend, primarily driven by technological R&D in scientific research-related industries and digital transformation in high-end manufacturing. Second, significant disparities exist in factor misallocation across the three sectors, with data factors demonstrating relatively moderate distortion compared to capital and labor. Third, output growth primarily depended on increased factor inputs, then by digital productivity growth and output share effects. Fourth, the factor price marketization mechanisms are imperfect. With factor externalities, there are positive distortionary effects of capital and data on output changes, whereas the distortionary effect of labor is either positive or negative.

Key words: Digital Economy, New Quality Productivity, Resource Misallocation, Decomposition of Output Changes, Factor Distortion Effects