我国玉米生产驱动因素贡献份额分析基于埃塔平方法（η2）

THE CONTRIBUTION SHARE OF DRIVING FACTORS ON MAIZE PRODUCTION IN CHINABASEDON ETA SQUARE METHOD（η2）

关键词:  玉米  生产  影响因素  贡献份额  埃塔平方法（η²）

Key words:  maize  production  influencing factors  contribution share  ETA square method

摘要:

目的 从气象、生产投入、社会经济、技术进步、政策五个方面对玉米生产的驱动因素进行定量分析，明确不同驱动因素对玉米生产的影响程度。方法 文章采用埃塔平方法（η²）对1978—2018年玉米生产数据进行分析，分别对全国和两大主产区建立全因素模型和局部因素模型群，测算各组因素的贡献份额。结果 （1）在全国全时段模型群中，技术进步因素对我国玉米生产的独立贡献份额最大，为2.71%，生产投入和社会经济因素次之，而政策因素的贡献份额最小。多因素的交互作用中，贡献份额最为突出的是由气象、生产投入、社会经济和技术进步四大因素组成的模型，对我国玉米生产交互贡献了19.78%。（2）在全国分时段模型群中，社会经济因素的贡献份额始终最大，对全国玉米的贡献作用最为显著。多因素的交互作用中，气象、生产投入、社会经济和技术进步因素组合模型的交互贡献份额在除20世纪80年代外均表现为最大，而1980时段气象、社会经济、技术进步和政策因素的交互贡献份额最大，为10.28%。（3）在分区域全时段模型群中，北方春玉米区的气象因素独立贡献份额最大，政策因素最小，而黄淮海夏玉米区的生产投入因素独立贡献份额最大，技术进步因素最小。多因素的交互作用中，北方春玉米区的气象、生产投入、社会经济和技术进步因素的交互贡献份额最大，而黄淮海夏玉米区的生产投入、社会经济、技术进步和政策因素的交互贡献份额最大。结论 在全国全时段中，技术进步、生产投入和社会经济因素对玉米生产影响显著，气象和政策因素的影响效应在多个因素的相互作用中有所削弱；在不同时段中，社会经济、技术进步因素的驱动作用始终较大，其中社会经济的驱动作用最为显著；不同区域受驱动因素的影响存在一定的差异，要因地制宜进行合理的玉米生产。

Abstract:

The objective of this study is to make a quantitative analysis of the driving factors of maize production from five aspects, namely meteorology, factor input, social economy, technological progress and policy, to determine the degree of influence of different driving factors on maize production. The data of maize production from 1978 to 2018 were analyzed by using ETA square method. And a total factor model and a local factor model group were established for the whole country and the two major producing areas, respectively, to calculate the contribution share of each group. The results of this study were showed as follows. (1) In the national whole-time model group, the independent contribution share of technological progress to China′s maize production was the largest, which was 2.71%, followed by factor input and socio-economic factors, while the contribution share of policy factors was the smallest. Among the interaction of multiple factors, the model with the most outstanding contribution share was composed of meteorological, factor input, social economy and technological progress, which contributed 19.78% to the interaction of China′s maize production. (2) In the national time-division model group, the contribution share of social and economic factors was always the largest, and the contribution to the national maize was the most significant. Among the interaction of multiple factors, the interactive contribution share of the combination model of meteorological, factor input, socio-economic and technological progress was always the largest except for the period of 1980, while the interactive contribution share of meteorological, socio-economic, technological progress and policy factors was the largest, which was 10.28% in 1980. (3) In the all-time sub-regional model group, the independent contribution of meteorological factors and policy factors in the Northern Spring Maize Region was the largest, while the independent contribution of factor input factors and technological progress factors in the Huang-Huai-Hai Summer Maize Region were the largest. Among the interaction of multiple factors, the interactive contribution of meteorological, factor input, social economy and technological progress in the Northern Spring Maize Region was the largest, while that of the Huang-Huai-Hai Summer Maize Region was the largest. The conclusion of this paper is that：In the whole period of the country, technological progress, factor input and socio-economic factors have a significant impact on maize production, and the impact of meteorological and policy factors is weakened in the interaction of multiple factors. In different periods of time, the driving effect of socio-economic and technological progress factors is always greater, among which the driving effect of socio-economic is the most significant. Different regions are affected by driving factors to some extent, so it is necessary to carry out reasonable maize production according to local conditions.