원문정보
초록
영어
Focusing on the phenomenon that rural land circulation has translated farmland into non-agricultural and non-grain land in recent years, this paper tries to theoretically solve the significant practical issue of sharp reduction in farmland caused by urbanization and grain security that is badly in need of solution in China through constructing models to study the relations between rural land circulation and grain security. As an important part of national security, grain security is a key strategic issue concerning national economy and the people’s livelihood. Grain security, energy security and financial security are called three major kinds of economic security in the world. In 2014, China’s grain output reached 607.10 million tons, seeing increases for 11 consecutive times, but the self-sufficiency rate of grain reduced to under 90%, and the grain supply gap continued to widen. To this end, the CPC Central Committee has proposed the new national grain security strategy of “Self-centered, state-based, capacity-guaranteed, and technology-supported with appropriate import” and taken important measures to strengthen land circulation and expand business scale. However, in theory, the issues whether agricultural production has scale operation and whether scale operation can increase grain output have remained controversial for a long time. In reality, China’s rural land circulation proportion in 2014 reached 28.8%, but the phenomena of non-grain farmland and non-agricultural farmland become serious. Therefore, this paper shows significance in both theory and practice with regard to the study on the relations between China’s grain security and rural land circulation as well as relevant policies. Through construction of Nerlove model of grain supply response, quantitative analysis is conducted to study the influences of rural land circulation on grain safety and relevant policies and suggestions are proposed in this paper.
목차
1. Introduction
2. Materials and Methods
2.1. Nerlove Model
2.2. Generalized Least Square (GLS)
2.3. Principle of ADF Test
2.4. Johansen Co-Integration Test
2.5. Model Analysis Procedure
3. Results and Discussion
3.1. Data Sources and Processing
3.2. Discussion
4. Conclusion
References