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Impact of advanced storage facilities on households’ maize storage losses and food security in China

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Abstract

Reducing post harvest losses has been an option to enhance food security. Hence, the Chinese government has implemented the “scientific grain storage project” to improve household storage conditions and reduce storage losses. Based on the data of 1202 rural households from 23 provinces in China, we used propensity score matching (PSM) to measure the effects of advanced storage facilities on household food security. The results reveal that advanced storage facilities significantly reduced household maize storage losses by 60%, allowing farmers to save 33 kg of maize (worth US$21) and reducing the maize storage loss rate from 2.85 to 0.87%. Adopters of advanced storage facilities stored their maize for 0.2 quarters longer and reduced the use of pesticides during storage. At the same time, using advanced storage facilities significantly strengthens household food security and reduces the proportion of market purchases to meet households’ food consumption. Moreover, the adoption of advanced storage facilities also has important implications for China’s national food security and resource conservation. Accordingly, the government should continue to encourage farmers to adopt advanced storage facility practices.

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Notes

  1. Source: National Food Administration “Guidance on the implementation of reduce post-harvest loss project” (in Chinese), https://www.ixueshu.com/document/c5951ac9594994eee62f786dd3a139e0318947a18e7f9386.html.

  2. Traditional storage facilities include wooden cabinets, stone cabinets, gunny or polypropylene (PP) bags, baskets and jars. Some farmers choose not to use any facilities, that is, to store in bulk.

  3. Different crops have different storage facilities; the advanced facilities suitable for maize storage include metal silos, brick concrete structure warehouses and steel frame warehouses. Considering a 1000-kg metal silo as an example, the market price is approximately 400 yuan (worth US$ 62).

  4. Data source: China Statistical Yearbook 2019.

  5. Food security include availability, access, stability and utilization. Due to data limitations, we choose the proportion of purchased food to total food consumption that indicates the stability of food security.

  6. Nearest neighbour matching matches a subject from the control group to a subject in the treatment group, based on the closest propensity score. In kernel matching, each person in the treatment group is matched to weighted averages of individuals who have similar propensity scores, with greater weight being given to people with closer scores. Radius matching uses a tolerance level on the maximum propensity score distance between a subject in the treatment group and all individuals in the control group who are within that distance (Caliendo and Kopeinig, 2008).

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Acknowledgements

We acknowledge the financial support from the special project on non-profit grain industry research, “Research on Investigation and Assessment Techniques for Post-Harvest Grain Loss and Waste” program, supported by the National Food and Strategic Reserves Administration and National Natural Science Foundation of China. We thank the district authorities in the study area and all those who were involved in data collection, analysis and report compilation.

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Authors and Affiliations

  1. Center for Price Cost Investigation, National Development and Reform Commission, Beijing, 100045, China

    Yi Luo

  2. Institute of Economics, Hunan Academy of Social Sciences, Changsha, Hunan, 410003, China

    Dong Huang

  3. College of Economics and Management, China Agricultural University, Beijing, 100083, China

    Haimin Miao, Laping Wu & Junfeng Zhu

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  1. Yi Luo
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  2. Dong Huang
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  3. Haimin Miao
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  4. Laping Wu
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Correspondence to Laping Wu.

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Appendix

Appendix

See Fig. 2 and Table 10.

Fig. 2
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Table 10 Variable definitions
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Luo, Y., Huang, D., Miao, H. et al. Impact of advanced storage facilities on households’ maize storage losses and food security in China. Environ Dev Sustain 24, 221–237 (2022). https://doi.org/10.1007/s10668-021-01406-z

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