数据流动规则与制造业出口技术复杂度

谢娟娟　肖姝帆

（南开大学）

内容提要：数据作为全球数字化的核心要素，其流动规则对制造业技术升级具有重要影响。本文基于欧洲国际政治经济中心（ECIPE）发布的数字贸易估算（DTE）数据库，构建了2000—2018年的数据政策指数，从数据流动规则的限制性视角系统考察数据流动规则对制造业出口技术复杂度的影响及其作用机制。研究结果表明，宽松的数据流动规则能够提升制造业出口技术复杂度；通过引入两个工具变量进行内生性分析，研究结果的稳健性得到进一步验证。异质性分析发现，不同行业类别及不同类型的数据流动规则对制造业出口技术复杂度的影响存在明显差异。机制分析进一步揭示，数据流动规则通过数字技术赋能效应、贸易成本降低效应以及外部需求提振效应三条渠道推动制造业出口技术复杂度的提升。根据研究结论，本文提出通过科学合理的数据流动规则释放数据要素潜能，推动制造业体系重构与技术迭代的政策建议。

关键词：数据流动规则；数据政策指数；制造业；出口技术复杂度；数字技术赋能

作者简介：谢娟娟，南开大学经济学院教授、博士生导师，天津，300071；肖姝帆，南开大学经济学院博士研究生，通信作者。

基金项目：国家社会科学基金一般项目“数字基础设施建设促进制造业数字化转型升级研究”（22BJY195）

引用格式：谢娟娟,肖姝帆.数据流动规则与制造业出口技术复杂度[J].经济与管理研究,2025,46(10):57-74.

Data Flow Regulations and Technological Complexity of Manufacturing Exports

XIE Juanjuan, XIAO Shufan

(Nankai University, Tianjin 300071)

Abstract: With the acceleration of global digitalization, data has emerged as a critical factor driving economic growth and technological advancement. To safeguard national security and protect personal privacy, countries have established institutional frameworks for data flow regulations across multiple dimensions, including cross-border transmission, data localization, and security reviews. Against this backdrop, a pressing issue is how to design scientific and reasonable data flow regulations that can unlock the potential of data as a production factor, thereby promoting the restructuring of the manufacturing system and facilitating technological upgrading. Therefore, this paper examines the issue from the perspective of data flow restrictions.

Drawing upon the ECIPE-DTE database, this paper constructs a data policy index covering 55 economies from 2000 to 2018. Then, it combines the index with panel data for manufacturing industries to systematically analyze the impact of data flow regulations on the technological complexity of manufacturing exports, as well as the underlying mechanisms. The empirical results demonstrate that more relaxed data flow regulations can increase the technological complexity of manufacturing exports. Specifically, three key mechanisms are highlighted: the digital technology enabling effect, the trade cost reduction effect, and the external demand boosting effect.

To empirically verify these mechanisms,this paper employs a multi-dimensional panel fixed effects model. The benchmark regression reveals that data flow regulations exert a positive effect on the technological complexity of manufacturing exports. To address potential endogeneity concerns, this paper constructs two instrumental variables—a weighted data policy index and mobile network coverage—and employs the two-stage least squares (2SLS) estimation method to validate the robustness of the findings. Mechanism tests further demonstrate that relaxed data flow regulations reinforce the digital technology enabling effect by increasing industrial robot density and stimulating R&D expenditure. Meanwhile, rational data flow regulations effectively reduce comprehensive trade costs, logistics costs, and search costs, thereby supporting the trade cost reduction effect. Furthermore, transparent and coordinated data flow regulations enhance the responsiveness of the supply side to global demand shifts, thereby confirming the external demand boosting effect.

The potential contributions are threefold. First, this paper takes data flow regulations as the analytical entry point and systematically investigates their effects on the technological complexity of manufacturing exports, highlighting both their restrictive and enabling dimensions. Second, it improves the measurement of data governance by constructing an extended data policy index panel dataset that enriches existing research in terms of temporal and spatial coverage. Third, it comprehensively identifies and empirically examines three critical channels through which data flow regulations influence the upgrading of manufacturing export structures.

Keywords: data flow regulations; data policy index; manufacturing; technological complexity of manufacturing exports; digital technology empowerment

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