This study examines the dynamic relationships among China’s grain production, total agricultural machinery power, urban construction area, and effective irrigated area from 2004 to 2023, employing VAR, cointegration analysis, VECM, Granger causality tests, and variance decomposition. The findings reveal a significant long-term equilibrium among the variables, with total agricultural machinery power and grain production exhibiting a bidirectional causal relationship. Variance decomposition highlights that grain production variability is initially driven by its own shocks, but over time, the influence of agricultural machinery power becomes increasingly significant. The study underscores the critical role of agricultural mechanization and infrastructure in sustaining grain production and provides valuable insights for policymakers to optimize resource allocation and design effective strategies for agricultural development.
목차
ABSTRACT I. Introduction II. Literature Review III. Methodology IV. Empirical Analysis 1. Data and Descriptive Statistics 2. Unit Root Test 3. Cointegration Test 4. Granger Causality Test 5. VECM Estimation 6. Variance Decomposition Analysis V. Conclusion and Policy Implications References
키워드
grain productiontotal agricultural machinery powerurban construction areaGranger causality analysisvector error correction model (VECM)
저자
Qu Meijing [ Ph. D. Candidate, Department of Advertising and Public Relations, Silla University ]
'KU 중국연구원'은 건국대학교만의 차별화된 가치를 구현하기 위해 건국대의 교시(校是)인 성(誠)·신(信)·의(義)를 바탕으로 인본(人本)·소통(疏通)·통섭(統攝)에 초점을 둔 중국학 연구를 지향하고 있습니다. 또한 시대적 당위성을 반영한 실용 중심의 연구와 학문 후속세대 양성에 기여하는 국제적 연구센터로 발돋음하는 연구기관 입니다.