Data Deepening and Nonbalanced Economic Growth

Abstract

As a newly emerging factor, data has been widely utilized in producing goods and services, and the nonbalanced growth between digital industries and non-digital industries is significant in recent years. In the digital economy, data has two unique features. One is the fact that data in one industry is the by-product of economic activities not only in its own industry but also in other industries, and it accumulates and depreciates like capital. Another is that, because of the strongly skilled-biased property, data only can be operated by skilled workers from high-tech companies. More importantly, data utilization within and across sectors can spur new ideas and promote technological innovation. We provide a novel growth model with two sectors differing in the degree of data deepening and the factor structure of production function. Our model indicates that an increase in data stock in two sectors has opposite effects on the allocation of skilled labor across sectors, and the skill premium (i.e., the wage of skilled labor relative to that of unskilled labor) decreases with an increase in the fraction of skilled labor employed in the data-extensive sector. With credible parameter values, model calibration shows that faster growth of output occurs in the more data-intensive sector and the high-level skill premium persists as the data accumulates in the long run.