Big data and inter-firm wage disparities: theory and evidence from China

While Big Data is driving high-quality firm development, it will also have a new impact on wage differences among firms, which is a less discussed topic in the literature. A theoretical model indicates that Big Data as an element-enhancing factor could influence inter-firm wage disparities by altering differences in productivity and the labor skill structure across firms. Taking data from Chinese A-share listed companies spanning from 2008 to 2022 and leveraging the establishment of National Comprehensive Big Data Pilot Zones (NCBDPZ) in China as an exogenous event, we employ a staggered DID model to empirically investigate the relationship between Big Data and inter-firm wage disparities. Our findings reveal that Big Data significantly reduces inter-firm wage disparities within the city. This conclusion remains robust after undergoing rigorous tests like parallel trend analysis and placebo tests. Mechanism analysis indicates that Big Data can narrow the inter-firm wage disparities by mitigating labor productivity and labor skill structure disparities among firms. Furthermore, our further analysis demonstrates that the reducing effect of Big Data on inter-firm wage disparities is primarily observed in the Secondary sector, with the most pronounced impact being within western regions in China. In addition, it is noteworthy that Big Data primarily enhances intra-distribution of labor income by alleviating wage disparities between firms rather than within. This study contributes to understanding how data elements can reshape income distribution structures, offering valuable insights for government entities seeking to strengthen the role of Big Data in reducing income disparities.