The evaluation of land consolidation policy in improving agricultural productivity in China
Abstract China is presently undergoing rapid economic development and unprecedented urbanization. Concerns over food security have prompted the Chinese government to implement large-scale land consolidation projects. However, no formal evaluation has been conducted on such projects. Thus, effectiven...
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Autores principales: | , , , , , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2017
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Materias: | |
Acceso en línea: | https://doaj.org/article/78fda00490d7407d9f9ac12a4102d1f7 |
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Sumario: | Abstract China is presently undergoing rapid economic development and unprecedented urbanization. Concerns over food security have prompted the Chinese government to implement large-scale land consolidation projects. However, no formal evaluation has been conducted on such projects. Thus, effectiveness of land consolidation policy remains uncertain. We obtained detailed geo-spatial information for 5328 land consolidation projects implemented between 2006 and 2010, and used time-series MODIS NDVI (2006–2016) data to assess effectiveness of China’s land consolidation policy in improving agricultural productivity. Our results show that the overall effectiveness of land consolidation in improving agricultural productivity is low, which lies in contrast to optimistic estimates based on regional statistical analysis and theoretical approaches. For projects (n = 560) implemented in 2006, about 29.5% showed significant (p < 0.05) increasing trends of MODIS NDVI after implementation of land consolidation. For 2007–2010, lower percentages (e.g., 25.9% in 2007 and 13.5% in 2010) of projects showed significant increasing trends. Furthermore, we found effectiveness of land consolidation projects displayed clear regional differences and driving factors are inconsistent with policy design. We anticipate our research to be a starting point for a more comprehensive evaluation involving longer time-series and higher spatial resolution data. |
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