关键词: 数字经济, 全要素生产率, 研发投入, 农产品加工业, 双向固定效应模型

Abstract:

[Objective] The agricultural product processing industry constitutes an important component in the economic system that plays a pivotal role in the construction of the entire agricultural industry chain and the realization of rural industrial revitalization. Despite China's agricultural product processing industry is experiencing the paradigm shift from a recovery-oriented development phase toward a high-quality development trajectory, but there remains a gap between its current status and both the strategic development targets and the industrial benchmarks established by advanced economies. The purpose of the research are: (1) Calculate the total factor productivity (TFP) within China's agricultural product processing industry to serve as a proxy variable for the high-quality development of the industry; (2) Identify the impact of the digital economy as an emerging economic paradigm on the total factor productivity of China's agricultural product processing industry and to elucidate the mediating role of research and development investment in this relationship; (3)Analyze the heterogeneous impacts of the digital economy on the TFP of the agricultural product processing industry across varying governance environments, business operational conditions and enterprise management proficiency levels. [Methods] First, based on the panel data of agricultural product processing related enterprises listed on China's A-share market from 2012 to 2024, the TFP was measured by the Solow residual approach and the Levinsohn-Petrin (LP) method. Through the comprehensive construction of an indicator system and the utilization of provincial-level panel data, the developmental level of the digital economy was systematically measured. Second, the study employed a two-way fixed effects model to identify the causal effect of the digital economy on TFP. In order to ensure the accuracy of data, robustness checks were conducted by replacing the baseline model with a Tobit model and by using alternative measures of the dependent variable.To address potential endogeneity, the one-period lagged value of digital economy development was used as an instrumental variable and the two-stage least squares (2SLS) method was adopted. In addition, a mediation model was introduced to test the channel effect of R&D expenditure. Finally, the heterogeneity of the digital economy's impact on total factor productivity was analyzed from the perspectives of digital government, the business environment and enterprise management expense ratios. [Results and Discussions] The digital economy can effectively enhance the total factor productivity of the agricultural product processing industry. Mechanism analysis indicated that the enterprise R&D investment played a partial mediating role in this relationship. These results remained robust after endogeneity treatment and robustness tests. Moreover, the impacts of the digital economy demonstrated significant heterogeneity when examined across different regional and enterprise dimensions. Specifically, with a relatively low level of digital government, the digital economy significantly inhibited the improvement of TFP; by contrast, with a more favorable business environment, the digital economy significantly promoted TFP growth. The conclusion demonstrated that only when digital government or business environment reaches advanced levels can they synergistically enhance the TFP of China's agricultural product processing industry with the digital economy. There was a significant negative relationship between management expense ratio and the impact of digital economy on TFP, which indicated enhancing management efficiency constituted a crucial pathway for improving firm-level total factor productivity. [Conclusions] Although the digital economy exerted substantial promotional impacts on the high-quality development of China's agricultural product processing industry, that still necessitated the attainment of specific thresholds across governmental governance environments, market operational conditions and enterprise management capabilities. Consequently, the efforts should be made to promote the deep integration between the digital economy and the agricultural product processing sector. On the one hand, the construction of digital government should be enhanced by extensively applying digital technologies to government service domains, implementing precision policy formulation to improve service accessibility and establishing stable, equitable, transparent and predictable policy and business environments for agricultural processing enterprises. On the other hand, agricultural processing enterprises should strategically leverage digital technologies to foster comprehensive innovation across technological, organizational and managerial dimensions, thereby realizing the optimization of their management tools and operational processes, the improvement of efficient resource allocation and utilization and the rational cost control. Ultimately in the modern digital economy landscape overall operational efficiency and competitive advantage of the agricultural product processing sector can be enhanced.

Key words: digital economy, total factor productivity, R&D investment, agricultural product processing industry, two-way fixed effects model