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陕西省耕地资源数量与经济发展关系的计量分析 被引量:5

Econometric Analysis of Relationship between Cultivated Land Quantity and Economic Development in Shaanxi Province
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摘要 基于1978—2005年陕西省耕地资源数量与经济发展的统计数据,运用协整分析、误差修正模型、脉冲响应函数和方差分解等方法分析了陕西省耕地资源数量与经济发展之间的互动关系,结果显示:1)陕西省耕地资源数量与经济发展之间存在长期均衡关系,但短期内却存在失衡,短期波动向长期均衡趋近的调整幅度为4.23%,调整力度非常小;2)经济发展的冲击可以部分解释耕地资源数量的变化,解释水平为12%以下,耕地资源数量的冲击对经济发展的解释水平在18%以下;3)耕地资源数量、经济发展均显著地受其自身波动的影响。建议从提升经济发展质量和耕地利用效率等方面采取长期性、综合性的政府干预措施。 Based on the statistical data of cultivated land quantity and economic development in Shaanxi Province during 1978-2005,using the method of co-integration analysis,error correction model,impulse response functions and variance decomposition,the interaction on cultivated land quantity and economic development in Shaanxi Province was analyzed in this paper,and it includes how to ease the conflicts between cultivated land protection and economic development.The results indicate that:1) There exist equilibrium relationship between cultivated land quantity and economic development in long term whereas they are different in short term, and the range of short term equilibrium close to long term equilibrium is 4. 23%, whicn is very small.2) The economic development impulse can partly explain the changes of cultivated land quantity to a certain extent of below 12%, the cultivated land quantity impulse can explain the change of economic development to a certain extent of below 18%. 3) The cultivated land quantity was influenced by its own fluctuation, and so did the economic development. Therefore, it is necessary to take long-term and comprehensive government intervention to harmonize cultivated land conservation with economic development such as improving the quality of economic development and land use efficiency.
作者 韩申山
出处 《地理与地理信息科学》 CSCD 北大核心 2009年第6期68-71,共4页 Geography and Geo-Information Science
基金 国家社科基金(07XSH017) 陕西省科技厅基金(07K03-01-2) 咸阳师范学院科研专项基金(08XSYK215)
关键词 耕地资源 经济发展 协整分析 误差修正模型 脉冲响应函数 方差分解 land resource economic development co-integration analysis error correction model impulse response function variance decomposition
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