Abstract

Breaking the “poverty trap” has gradually become the core topic of economic research. The transformation and upgrading of industrial structure is considered an essential means to break the “poverty trap”. How to use the digital economy effect to change the allocation of capital and labor factors and realize the transformation and upgrading of industrial structure is a significant issue in this paper. The study focuses on examining the development of China’s digital economy between 2013 and 2021, uses the entropy method to measure it, and conducts an empirical study through a fixed-effects model and an intermediary-effect model to investigate the influence and mechanism of the digital economy on industrial structure transformation and upgrading. The results indicate the following: Firstly, the digital economy plays a crucial role in facilitating the transformation and upgrading of industrial structure, and this conclusion was still robust even after controlling for a series of factors affecting the transformation and upgrading of industrial structure and correcting the endogenous estimation deviation by using instrumental variables. Secondly, through the heterogeneity analysis of regions with different economic development levels, it was found that compared with economically developed regions, economically backward regions need to pay more attention to the development of the digital economy. Thirdly, the examination of the mechanism revealed that the digital economy has realized the transformation and upgrading of industrial structure by optimizing the allocation of capital and labor. In this paper, Schumpeter’s innovation theory is regarded as a new perspective to break the “poverty trap” and realize the transformation and upgrading of industrial structure, filling the gap in related research in this field. This study provides a suggestion for economically backward areas to break the “poverty trap” and provides theoretical support and practical guidance for the sustained economic growth of the whole country.

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