How Does the Low-Altitude Economy Drive Total Factor Productivity in Enterprises?—A Study Based on Machine Learning Methods and a DID Empirical Model

Jiayuan Wen; Zijie Wang; Joanna Rosak-Szyrocka; Grzegorz Mentel

Abstract

As a new paradigm of productivity, the low-altitude economy (LAE) is increasingly demonstrating its strategic importance. By applying a machine learning dictionary approach to corporate reports and patents, this study finds that LAE significantly enhances firms’ total factor productivity (TFP). This effect operates primarily through industrial integration and R&D activities, and is particularly evident in high-tech, manufacturing, and high-pollution firms, as well as in improvements in firm value. Further evidence from the National Big Data Pilot verifies its dynamic impact. The main innovation of this paper lies in quantifying the policy concept of “low-altitude economy” as measurable firm-level TFP gains, thereby filling the gap in micro-level empirical evidence. In addition, the publicly available LAE dictionary and multidimensional indicators provide new research and regulatory tools for academia and policymakers. The results suggest that priority should be given to subsidies and airspace hierarchy reforms in high-tech, manufacturing, and high-pollution industries, fostering synergies between digital infrastructure and airspace liberalization, reducing capital market risk premiums, and accelerating the commercialization of the entire chain of new energy aircraft, urban air mobility, and aerospace information services. Therefore, LAE urgently requires a full-chain, market-oriented policy framework and upgraded airspace regulations.

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