农业工程学报
農業工程學報
농업공정학보
2015年
2期
1-6
,共6页
粮食%作物%农业%对数均值迪氏指数法%产量%影响因素%分解%无残差
糧食%作物%農業%對數均值迪氏指數法%產量%影響因素%分解%無殘差
양식%작물%농업%대수균치적씨지수법%산량%영향인소%분해%무잔차
grain%crops%agriculture%logarithmic mean divisia index (LMDI)%yield%influencing factors%decomposition%non-residual
为了明确不同因素对粮食产量变化影响的大小,分析粮食产量波动变化的机理,该文采用对数均值迪氏指数法建立了粮食产量无残差因素分解模型,将中国粮食产量的波动分解为播面单产、种植结构、复种指数和耕地面积变化的贡献。基于1996-2012年数据,对该期间影响中国粮食产量波动的因素进行了分解,结果表明:播面单产和复种指数的变化表现为增长效应,种植结构和耕地面积的变化表现为减量效应,其中播面单产变化促进粮食产量增长8592.25万t,对粮食产量增长的贡献率为101.03%;复种指数变化促进粮食产量增长6926.97万t,对粮食产量增长的贡献为率81.45%;种植结构变化导致粮食产量减少3909.11万t,对粮食产量增长的贡献率为?45.97%;耕地面积变化导致粮食产量减少3105.61万t,对粮食产量增长的贡献率为?36.52%。各影响因子的作用具有阶段性,1996-2003年种植结构效应对粮食产量波动的影响较大;2004-2007年,播面单产、种植结构、复种指数的贡献相互交替,2004年播面单产的贡献最大,2005年、2007年复种指数的贡献最大,2006年则是种植结构的贡献最大;2008年开始播面单产效应起着主导作用。该研究可为政府有关部门粮食生产发展规划和相关产业政策的制定提供数据参考和理论依据。
為瞭明確不同因素對糧食產量變化影響的大小,分析糧食產量波動變化的機理,該文採用對數均值迪氏指數法建立瞭糧食產量無殘差因素分解模型,將中國糧食產量的波動分解為播麵單產、種植結構、複種指數和耕地麵積變化的貢獻。基于1996-2012年數據,對該期間影響中國糧食產量波動的因素進行瞭分解,結果錶明:播麵單產和複種指數的變化錶現為增長效應,種植結構和耕地麵積的變化錶現為減量效應,其中播麵單產變化促進糧食產量增長8592.25萬t,對糧食產量增長的貢獻率為101.03%;複種指數變化促進糧食產量增長6926.97萬t,對糧食產量增長的貢獻為率81.45%;種植結構變化導緻糧食產量減少3909.11萬t,對糧食產量增長的貢獻率為?45.97%;耕地麵積變化導緻糧食產量減少3105.61萬t,對糧食產量增長的貢獻率為?36.52%。各影響因子的作用具有階段性,1996-2003年種植結構效應對糧食產量波動的影響較大;2004-2007年,播麵單產、種植結構、複種指數的貢獻相互交替,2004年播麵單產的貢獻最大,2005年、2007年複種指數的貢獻最大,2006年則是種植結構的貢獻最大;2008年開始播麵單產效應起著主導作用。該研究可為政府有關部門糧食生產髮展規劃和相關產業政策的製定提供數據參攷和理論依據。
위료명학불동인소대양식산량변화영향적대소,분석양식산량파동변화적궤리,해문채용대수균치적씨지수법건립료양식산량무잔차인소분해모형,장중국양식산량적파동분해위파면단산、충식결구、복충지수화경지면적변화적공헌。기우1996-2012년수거,대해기간영향중국양식산량파동적인소진행료분해,결과표명:파면단산화복충지수적변화표현위증장효응,충식결구화경지면적적변화표현위감량효응,기중파면단산변화촉진양식산량증장8592.25만t,대양식산량증장적공헌솔위101.03%;복충지수변화촉진양식산량증장6926.97만t,대양식산량증장적공헌위솔81.45%;충식결구변화도치양식산량감소3909.11만t,대양식산량증장적공헌솔위?45.97%;경지면적변화도치양식산량감소3105.61만t,대양식산량증장적공헌솔위?36.52%。각영향인자적작용구유계단성,1996-2003년충식결구효응대양식산량파동적영향교대;2004-2007년,파면단산、충식결구、복충지수적공헌상호교체,2004년파면단산적공헌최대,2005년、2007년복충지수적공헌최대,2006년칙시충식결구적공헌최대;2008년개시파면단산효응기착주도작용。해연구가위정부유관부문양식생산발전규화화상관산업정책적제정제공수거삼고화이론의거。
The premise for establishment of appropriate grain production policies is to analyze the contributions of different influence factors to the variation of grain production. However, the existing studies focus on the overall comparison of influence factors affecting the grain production in China, and thus cannot reflect the annual differences or changes. Therefore, in this study, we built a complete (zero residual) decomposition model based on logarithmic mean Divisia index (LMDI) method for investigation into grain production in China. With this model, the changes of grain production were decomposed into the contributions from four factors, including yield per cultivated area, planting structure, multi-cropping index, and changes of cultivated land area. Based on the data from 1996 to 2012, we decomposed and analyzed the factors affecting the changes of grain production in China during this period. The results showed that the total grain production in China generally increased from 1996 to 2012, but it also fluctuated at a severe rate inter-annually. From the perspective of increments, the effect size of yield per cultivated area was 85.9225 million t, and yield per cultivated area was a major influence factor promoting the increments of grain production in China. The effect size of planting structure was -39.0911 million t, and planting structure was a major influence factor inhibiting the increments of grain production in China. However, the effect of planting structure on grain production became strongly positive from 2004 to 2006, and planting structure was a major influence factor promoting the increments of grain production during this period. From the perspective of fluctuation, the fluctuation of grain production in China from 1996 to 2003 was mainly attributed to the effect of yield per cultivated area and the effect of planting structure. From 2004 to 2007, the effects of yield per cultivated area, planting structure and multi-cropping index on grain production were contributive alternatively, but no effect was absolutely dominant. Since 2008, the effect of yield per cultivated area and the total effect changed in very similar ways. The results above show that the effect of yield per cultivated area is mainly responsible for the changes of grain production in China at the current stage, while the effect of planting structure can be enhanced greatly in the future. Moreover, the effect of multi-cropping index will not bring about great changes, but its sudden reduction may cause fluctuation. In comparison, the effect of cultivated land area can be ignored. Thus, regarding how to enhance China's grain production ability in the future, the main developing trends are to stably improve the yield per cultivated area, to raise the enthusiasm of peasants for grain production, to modify the planting structure, to prevent natural disasters, and to avoid the abrupt changes of multi-cropping index. These findings provide some valuble information for relevant governmental departments to establish grain production development plans and to formulate related industrial policies.