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In recent years China has taken on a huge challenge: modernize without destroying the environment. To see if "Big Data" policies work, researchers examined data from 30 provinces between 2009 and 2021. They used two advanced statistical tools – spatial difference‑in‑differences (SDID) and double machine learning (DML) – to compare regions with so‑called Big Data pilot zones to those without.

The findings are striking: pilot zones have sped up sustainable modernization and created spill‑over effects, spreading good practices to neighboring provinces. Moreover, a financial ecosystem that backs science and technology (the "eco‑finance") amplifies these effects.

Wealthier eastern provinces, already more innovation‑oriented, benefited the most, as did areas launching urban‑rural integration or green‑finance projects. The mechanism is clear: Big Data improve information gathering, let the government act faster, foster inclusive AI development, boost green‑innovation efficiency, and push industries to transform.

In practice, data become a kind of "collective brain" guiding China toward cleaner, smarter growth, showing that technology and environment can walk hand in hand.

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The analysis relies on a spatial difference‑in‑differences (SDID) model which, unlike the traditional DID, incorporates interactions among geographic units. This approach captures spill‑over effects, i.e., how innovations introduced in one province affect neighboring provinces through channels such as talent migration, shared digital infrastructure, and supply‑chain linkages. Double machine learning (DML) was employed to handle the high number of potentially confounding covariates, such as education level, industrial density, local environmental policies, and per‑capita GDP variations. DML combines machine‑learning regressions (e.g., random forest, gradient boosting) with an orthogonalization procedure, ensuring robust estimates even under high dimensionality.

Results show that Big Data pilot zones raise the sustainable modernization score by roughly 0.12 standardized points, with an influence radius of 200 km. Interaction with eco‑finance amplifies this effect by about 30%, suggesting that access to green‑focused capital enhances the ability of digital technologies to generate positive environmental impacts. Heterogeneity analysis reveals that eastern provinces, with higher 5G penetration and a larger share of tech start‑ups, experience stronger effects. Moreover, urban‑rural integration reforms facilitate the diffusion of open‑data platforms, lowering informational barriers between metropolitan and rural areas. The transmission mechanism operates through three main channels: (i) improved governance via real‑time monitoring systems, (ii) accelerated adoption of green production practices through predictive analytics, and (iii) sectoral restructuring, where high‑energy‑intensity sectors shift toward data‑driven, automated models. These findings support the hypothesis that the synergy between big data and eco‑finance acts as a catalyst for sustainable modernization, offering a replicable roadmap for other developing nations.

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Authors:
Qi LiuTianning GuanSiyu LiuJuncheng JiaChenxuan YuKun Lv
Date Published:
Original Article www.mdpi.com
Fact-check verified on 06/04/2026
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Creative Commons License CC BY-NC-SA 4.0

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