Can the pilot of national park system promote industrial agglomeration? double machine learning analysis taking Wuyishan tea industry as an example

The national park system pilot program is a significant initiative in China's ecological civilization institutional reform, and its impact on regional industrial development warrants further exploration. This study utilizes county-level data on tea industry enterprise registration from 2000 to 2022 and innovatively employs Double Machine Learning (DML) model to assess the impact of the national park system pilot program on tea industry aggregation within Wuyishan National Park, examining both horizontal and vertical aggregation dimensions. The research findings indicate the following: (1) The national park system pilot program has significantly promoted horizontal clustering and vertical integration of the tea industry in Wuyishan National Park. After removing outliers, resetting the sample division ratio, and changing the machine learning algorithm, the model results remain robust and reliable. (2) The national park system pilot program can promote tea industry clustering by strengthening fiscal support, technological innovation, and ecological protection. (3) The pilot program has a stronger impact on tea industry clustering in counties with higher economic levels and higher informatization levels. (4) The spatial distribution of horizontal and vertical agglomeration in the tea industry exhibits significant spatial autocorrelation. This study contributes to research on the economic effects of the national park system pilot program and provides theoretical support and practical insights for the green clustering development of agricultural industries.

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Publication Details

Journal
Frontiers in Sustainable Food Systems
Published
2025-11-28
DOI
https://doi.org/10.3389/fsufs.2025.1685204
Primary Topic
Advanced Technologies in Various Fields
Type
article
Field-Weighted Citation Impact
0.00

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article

Can the pilot of national park system promote industrial agglomeration? double machine learning analysis taking Wuyishan tea industry as an example

Qiao Chen, Bin Liang
Frontiers in Sustainable Food Systems
Advanced Technologies in Various Fields
article

Can the pilot of national park system promote industrial agglomeration? double machine learning analysis taking Wuyishan tea industry as an example

Qiao Chen, Bin Liang
article en

Abstract

The national park system pilot program is a significant initiative in China's ecological civilization institutional reform, and its impact on regional industrial development warrants further exploration. This study utilizes county-level data on tea industry enterprise registration from 2000 to 2022 and innovatively employs Double Machine Learning (DML) model to assess the impact of the national park system pilot program on tea industry aggregation within Wuyishan National Park, examining both horizontal and vertical aggregation dimensions. The research findings indicate the following: (1) The national park system pilot program has significantly promoted horizontal clustering and vertical integration of the tea industry in Wuyishan National Park. After removing outliers, resetting the sample division ratio, and changing the machine learning algorithm, the model results remain robust and reliable. (2) The national park system pilot program can promote tea industry clustering by strengthening fiscal support, technological innovation, and ecological protection. (3) The pilot program has a stronger impact on tea industry clustering in counties with higher economic levels and higher informatization levels. (4) The spatial distribution of horizontal and vertical agglomeration in the tea industry exhibits significant spatial autocorrelation. This study contributes to research on the economic effects of the national park system pilot program and provides theoretical support and practical insights for the green clustering development of agricultural industries.

Frontiers in Sustainable Food SystemsVol. 9
Hubei University Of Economics (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 80%
Advanced Technologies in Various Fields
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Can the pilot of national park system promote industrial agglomeration? double machine learning analysis taking Wuyishan tea industry as an example — Qiao Chen, Bin Liang · Frontiers in Sustainable Food Systems (2025) | TGRS Research Map | TGRS