Support policy preferences of grain family farms: evidence from Huang-huai-hai plain of China
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MSc candidate, Research Center for Food Safety and Agricultural Green Development, Qufu Normal University, Yantai Road 80#, Rizhao, Shandong, China P.R.
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Professor, Research Center for Food Safety and Agricultural Green Development, Qufu Normal University, Yantai Road 80#, Rizhao, Shandong, China P.R.
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This study uses the choice experiment method with 570 grain family farms located in the Huang-huai-hai Plain and determine various support policy attributes and the attribute levels for the two dimensions of policy measures and policy communication channels. Ordering effects are eliminated by warming up subjects in advance and using information disclosure. This paper uses the inferred attribute non-attendance method to process attributes ignored by the grain family farms and analyzes grain family farms’ preferences for different support policies with a mixed logit model and then uses a latent class model to analyze how the characteristics of grain family farms relate to different preference types. We find that grain family farms have a strong preference for agricultural subsidies, credit support, and technical support (the mean coefficient is greater than 0.8). Moreover, the preferences of grain family farms over the policy communication channel (the mean coefficient is greater than 0.5) cannot be ignored. Faced with the same policy attribute combination, grain family farms with high education levels, reasonable scales of operation, and good understanding of support policies are more likely to improve their profit margins. There are four preference types of grain family farms: finance preference (43.2%), knowledge and technology preference (28.5%), land transfer preference (15.4%), and policy information preference (12.9%).
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Support policy preferences of grain family farms: evidence from Huang-huai-hai plain of China
In: International Food and Agribusiness Management ReviewSearch for other papers by Lili Yu in
Current site
Google Scholar
PubMed
MSc candidate, Research Center for Food Safety and Agricultural Green Development, Qufu Normal University, Yantai Road 80#, Rizhao, Shandong, China P.R.
Search for other papers by Ziheng Niu in
Current site
Google Scholar
PubMed
Professor, Research Center for Food Safety and Agricultural Green Development, Qufu Normal University, Yantai Road 80#, Rizhao, Shandong, China P.R.
Search for other papers by Shijiu Yin in
Current site
Google Scholar
PubMed
Professor, Research Center for Food Safety and Agricultural Green Development, Qufu Normal University, Yantai Road 80#, Rizhao, Shandong, China P.R.
Search for other papers by Yang Gao in
Current site
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PubMed
Search for other papers by Borui Tian in
Current site
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PubMed
This study uses the choice experiment method with 570 grain family farms located in the Huang-huai-hai Plain and determine various support policy attributes and the attribute levels for the two dimensions of policy measures and policy communication channels. Ordering effects are eliminated by warming up subjects in advance and using information disclosure. This paper uses the inferred attribute non-attendance method to process attributes ignored by the grain family farms and analyzes grain family farms’ preferences for different support policies with a mixed logit model and then uses a latent class model to analyze how the characteristics of grain family farms relate to different preference types. We find that grain family farms have a strong preference for agricultural subsidies, credit support, and technical support (the mean coefficient is greater than 0.8). Moreover, the preferences of grain family farms over the policy communication channel (the mean coefficient is greater than 0.5) cannot be ignored. Faced with the same policy attribute combination, grain family farms with high education levels, reasonable scales of operation, and good understanding of support policies are more likely to improve their profit margins. There are four preference types of grain family farms: finance preference (43.2%), knowledge and technology preference (28.5%), land transfer preference (15.4%), and policy information preference (12.9%).
| All Time | Past 365 days | Past 30 Days | |
|---|---|---|---|
| Abstract Views | 0 | 0 | 0 |
| Full Text Views | 443 | 142 | 9 |
| PDF Views & Downloads | 160 | 80 | 3 |
