黄淮海地区县域粮食单产的空间溢出效应及影响因素分析
该研究运用马尔科夫链和空间马尔科夫链方法探讨了1980-2010年黄淮海地区347个县域粮食单产的溢出效应;并借助空间滞后模型揭示1995和2010年粮食单产分异的影响因素,以期为粮食生产布局优化和粮食生产提升政策制定提供依据。结果表明：1）35 a间黄淮海地区县域粮食单产转移总体呈现渐进、平滑的特征,大规模跨越的几率较低。2）似然比统计量分析表明,在1980-1995年和1995-2010年2个时段,区域背景对县域粮食单产类型转移格局的影响显著,且在1995-2010年更显著。中低产或中高产类型县域的粮食单产类型以平稳转移为主,而高产和低产类型县域在区域背景的作用下逐渐向中产类型转变。3）在...
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| Published in | 农业工程学报 Vol. 32; no. 9; pp. 299 - 307 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
北京农业信息技术研究中心,北京,100097%国家农业信息化工程技术研究中心,北京,100097%农业部农业信息技术重点实验室,北京,100097%北京市农业物联网工程技术研究中心,北京,100097
2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.2016.09.042 |
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| Abstract | 该研究运用马尔科夫链和空间马尔科夫链方法探讨了1980-2010年黄淮海地区347个县域粮食单产的溢出效应;并借助空间滞后模型揭示1995和2010年粮食单产分异的影响因素,以期为粮食生产布局优化和粮食生产提升政策制定提供依据。结果表明：1）35 a间黄淮海地区县域粮食单产转移总体呈现渐进、平滑的特征,大规模跨越的几率较低。2）似然比统计量分析表明,在1980-1995年和1995-2010年2个时段,区域背景对县域粮食单产类型转移格局的影响显著,且在1995-2010年更显著。中低产或中高产类型县域的粮食单产类型以平稳转移为主,而高产和低产类型县域在区域背景的作用下逐渐向中产类型转变。3）在空间格局演进方面,平原地带上移概率增加,而市辖区和沿海一带下移趋势明显,江苏、河南和山东3省的县域粮食单产类型趋于稳定。4）空间滞后模型计算结果表明,1995年,上一期粮食单产、农民人均纯收入、有效灌溉面积比率、产业结构对粮食单产的正向促进作用显著,分别通过1%的显著性水平检验;2010年,上一期粮食单产、农民人均纯收入和种植结构分别通过1%、1%、5%水平的显著性检验,而且上一期粮食单产和农民人均纯收均对粮食单产的正面推动作用显著。 |
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| AbstractList | F301.11%F304.5; 该研究运用马尔科夫链和空间马尔科夫链方法探讨了1980－2010年黄淮海地区347个县域粮食单产的溢出效应；并借助空间滞后模型揭示1995和2010年粮食单产分异的影响因素，以期为粮食生产布局优化和粮食生产提升政策制定提供依据。结果表明：1）35 a间黄淮海地区县域粮食单产转移总体呈现渐进、平滑的特征，大规模跨越的几率较低。2）似然比统计量分析表明，在1980－1995年和1995－2010年2个时段，区域背景对县域粮食单产类型转移格局的影响显著，且在1995－2010年更显著。中低产或中高产类型县域的粮食单产类型以平稳转移为主，而高产和低产类型县域在区域背景的作用下逐渐向中产类型转变。3）在空间格局演进方面，平原地带上移概率增加，而市辖区和沿海一带下移趋势明显，江苏、河南和山东3省的县域粮食单产类型趋于稳定。4）空间滞后模型计算结果表明，1995年，上一期粮食单产、农民人均纯收入、有效灌溉面积比率、产业结构对粮食单产的正向促进作用显著，分别通过1%的显著性水平检验；2010年，上一期粮食单产、农民人均纯收入和种植结构分别通过1%、1%、5%水平的显著性检验，而且上一期粮食单产和农民人均纯收均对粮食单产的正面推动作用显著。 该研究运用马尔科夫链和空间马尔科夫链方法探讨了1980-2010年黄淮海地区347个县域粮食单产的溢出效应;并借助空间滞后模型揭示1995和2010年粮食单产分异的影响因素,以期为粮食生产布局优化和粮食生产提升政策制定提供依据。结果表明：1）35 a间黄淮海地区县域粮食单产转移总体呈现渐进、平滑的特征,大规模跨越的几率较低。2）似然比统计量分析表明,在1980-1995年和1995-2010年2个时段,区域背景对县域粮食单产类型转移格局的影响显著,且在1995-2010年更显著。中低产或中高产类型县域的粮食单产类型以平稳转移为主,而高产和低产类型县域在区域背景的作用下逐渐向中产类型转变。3）在空间格局演进方面,平原地带上移概率增加,而市辖区和沿海一带下移趋势明显,江苏、河南和山东3省的县域粮食单产类型趋于稳定。4）空间滞后模型计算结果表明,1995年,上一期粮食单产、农民人均纯收入、有效灌溉面积比率、产业结构对粮食单产的正向促进作用显著,分别通过1%的显著性水平检验;2010年,上一期粮食单产、农民人均纯收入和种植结构分别通过1%、1%、5%水平的显著性检验,而且上一期粮食单产和农民人均纯收均对粮食单产的正面推动作用显著。 |
| Abstract_FL | As an important grain production base of China, Huang-Huai-Hai region is of great significance for the steady grain supply of the country. Under the strategic background of regional cooperative development, the spatial externality of grain yield per hectare has attracted increasing attention. In order to investigate the spillover effects of grain yield per hectare at county level, this study focuses on the 347 counties of Huang-Huai-Hai region by Markov Chain method and Spatial Markov Chain method, and reveals the spatial spillover effect of grain yield per hectare at county level during 1980-2010 as well as the influential factors of the differentiation of grain yield in 1995 and 2010. And the results show: 1) During 1980-2010, the type of grain yield per hectare at county level in Huang-Huai-Hai region transfers in a gradual and smooth way, with a low probability of large-scale crossing. 2) During 1980-1995, the likelihood ratio statistic is 52.198, passing the Chi-square test with the significance level of 0.01, and is 55.147, passing the Chi-square test with the significance level of 0.005 during 1995-2010. That is to say the regional background type exerts significant impact on the type shifting of grain yield per hectare, and it’s more significant in the second stage. The growth of grain yield per hectare of the counties at medium-low or medium-high level is similar, while the counties with high yield and low yield under the action of the regional context, gradually change toward middle type. Taking the counties adjacent to the high grain yield for example, their grain yield types per hectare will have a relative high possibility to increase, and vice versa. 3) In the aspect of spatial pattern of evolution, the type of grain yield per hectare tends to increase in the plain, and reduce obviously in the municipal districts and the coastal area. However, the type of grain yield per hectare in Jiangsu, Henan and Shandong Province gradually transfers to be stable. 4) Variations like grain yield per unit area in the last stage, average net income of peasant, industrial structure and ratio of effective irrigated areas have great impacts on the differentiation of grain yield per hectare at county level. And the influencing direction and degree of the factors in 1995 and 2010 are significantly different. In 1995, grain yield per hectare in the last stage, average net income of peasant, ratio of effective irrigated areas and industrial structure have passed the test of the significance level of 0.01, separately, and these indices are significantly positive to promote the grain yield; in 2010, the index of grain yield per hectare in the last stage, average net income of peasant and plant structure goes through the significant test, and the significance level is 0.01, 0.01 and 0.05, respectively. Except the average net income of peasant, the rest both play a positive role in promoting the overflow yield. These results can provide scientific ground for the optimization of grain production and policy-making to increase the grain yield per hectare in Huang-Huai-Hai region. |
| Author | 刘玉 唐秀美 潘瑜春 唐林楠 |
| AuthorAffiliation | 北京农业信息技术研究中心,北京100097 国家农业信息化工程技术研究中心,北京100097 农业部农业信息技术重点实验室,北京100097 北京市农业物联网工程技术研究中心,北京100097 |
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| Author_FL | Tang Xiumei Liu Yu Pan Yuchun Tang Linnan |
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| DocumentTitleAlternate | Analysis on spatial spillover effect and influence factors of grain yield per hectare at county level in Huang-Huai-Hai region |
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| Keywords | 空间滞后模型 models yield per hectare spatial lag model 模型 spatial spillover effect 空间溢出效应 空间马尔科夫链 optimization 优化 单产 grain Huang-Huai-Hai region 黄淮海地区 spatial Markov chain 粮食 |
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| Notes | 11-2047/S As an important grain production base of China, Huang-Huai-Hai region is of great significance for the steady grain supply of the country. Under the strategic background of regional cooperative development, the spatial externality of grain yield per hectare has attracted increasing attention. In order to investigate the spillover effects of grain yield per hectare at county level, this study focuses on the 347 counties of Huang-Huai-Hai region by Markov Chain method and Spatial Markov Chain method, and reveals the spatial spillover effect of grain yield per hectare at county level during 1980-2010 as well as the influential factors of the differentiation of grain yield in 1995 and 2010. And the results show： 1） During 1980-2010, the type of grain yield per hectare at county level in Huang-Huai-Hai region transfers in a gradual and smooth way, with a low probability of large-scale crossing. 2） During 1980-1995, the likelihood ratio statistic is 52.198, passing the Chi-square test with the significance |
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| Publisher | 北京农业信息技术研究中心,北京,100097%国家农业信息化工程技术研究中心,北京,100097%农业部农业信息技术重点实验室,北京,100097%北京市农业物联网工程技术研究中心,北京,100097 |
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| Snippet | 该研究运用马尔科夫链和空间马尔科夫链方法探讨了1980-2010年黄淮海地区347个县域粮食单产的溢出效应;并借助空间滞后模型揭示1995和2010年粮食单产分异的影响因素,以期为... F301.11%F304.5; 该研究运用马尔科夫链和空间马尔科夫链方法探讨了1980－2010年黄淮海地区347个县域粮食单产的溢出效应；并借助空间滞后模型揭示1995和2010年粮食单产分异... |
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| SubjectTerms | 优化 单产 模型 空间溢出效应 空间滞后模型 空间马尔科夫链 粮食 黄淮海地区 |
| Title | 黄淮海地区县域粮食单产的空间溢出效应及影响因素分析 |
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