Measurement and Regional Disparities of Pig Farming Efficiency Under Different Production Scales: Evidence From China

ABSTRACT China's pig farming sector is increasingly shifting toward large‐scale and intensive operations, and differences in productivity across farm‐size categories have become crucial for maintaining competitiveness. This paper investigates the changing scale structure of pig production and assesses both static efficiency and dynamic total factor productivity (TFP) for farms of four sizes using panel data from 27 mainland provinces for the period 2010–2022. Static efficiency is estimated using an input‐oriented Data Envelopment Analysis (DEA) model under variable returns to scale, specifically the Banker‐Charnes‐Cooper (BCC) specification, while dynamic productivity change is captured by the DEA‐based Malmquist index and its decomposition. The findings reveal that average static technical efficiency remains high, with medium‐sized farms slightly outperforming others. Large‐scale farms suffered a transient dip under external shock conditions, but subsequently recovered, largely through gains in pure technical efficiency. On the dynamic side, TFP hovered around unity, with technological progress emerging as the dominant driver of efficiency improvement. Regionally, eastern coastal provinces leveraged technological advancement to enhance productivity, whereas central and western regions were held back by persistent high‐input/low‐conversion inefficiencies. The results suggest that enhancing technological capacity and management performance, combined with region‐specific strategies supporting optimal scale development and technology diffusion, are key to narrowing regional gaps and promoting the high‐quality, sustainable development of China's pig‐farming industry.

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Publication Details

Journal
Agricultural Economics
Published
2026-02-26
DOI
https://doi.org/10.1111/agec.70105
Primary Topic
Efficiency Analysis Using DEA
Type
article
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article

Measurement and Regional Disparities of Pig Farming Efficiency Under Different Production Scales: Evidence From China

Gang Wu, Weiduo Chen, Shu Wang
Agricultural Economics
Efficiency Analysis Using DEA
article

Measurement and Regional Disparities of Pig Farming Efficiency Under Different Production Scales: Evidence From China

Gang Wu, Weiduo Chen, Shu Wang
article en

Abstract

ABSTRACT China's pig farming sector is increasingly shifting toward large‐scale and intensive operations, and differences in productivity across farm‐size categories have become crucial for maintaining competitiveness. This paper investigates the changing scale structure of pig production and assesses both static efficiency and dynamic total factor productivity (TFP) for farms of four sizes using panel data from 27 mainland provinces for the period 2010–2022. Static efficiency is estimated using an input‐oriented Data Envelopment Analysis (DEA) model under variable returns to scale, specifically the Banker‐Charnes‐Cooper (BCC) specification, while dynamic productivity change is captured by the DEA‐based Malmquist index and its decomposition. The findings reveal that average static technical efficiency remains high, with medium‐sized farms slightly outperforming others. Large‐scale farms suffered a transient dip under external shock conditions, but subsequently recovered, largely through gains in pure technical efficiency. On the dynamic side, TFP hovered around unity, with technological progress emerging as the dominant driver of efficiency improvement. Regionally, eastern coastal provinces leveraged technological advancement to enhance productivity, whereas central and western regions were held back by persistent high‐input/low‐conversion inefficiencies. The results suggest that enhancing technological capacity and management performance, combined with region‐specific strategies supporting optimal scale development and technology diffusion, are key to narrowing regional gaps and promoting the high‐quality, sustainable development of China's pig‐farming industry.

Agricultural EconomicsVol. 57(2)
Jinan University (CN), Institute of Agricultural Economics and Development (CN), Chinese Academy of Agricultural Sciences (CN)
Openalex Percentile: Top 37%
Efficiency Analysis Using DEA
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