基于区间型数据计量的我国粮食产量研究

doi:10.16088/j.issn.1001-6600.2021060914

Abstract

Abstract: Four modeling methods of interval data are used to explore the comprehensive impact of climate change and agricultural production input factors on China’s grain yield from 1993 to 2018. In addition, five evaluation indexes are used to measure the prediction accuracy of methods and the regression results are given and compared. The optimal regression method is applied to predict the change of grain yield in China. The results show that there are regional differences in grain yield in China, and the grain yield per unit area in some provinces changed greatly before 2009. But the grain yield per unit area of China’s eight provinces has tended to stable in the past tent years. Furthermore, climate change and agricultural production input factors have statistical significance in China’s grain yield. Finally, some suggestions are given to improve grain yield.

Key words: interval data, panel data, regression analysis, grain yield, climate change, agricultural production input factor

CLC Number:

O212.4

LI Chengen, PAN Xiaoying, WANG Meihan, SHI Jianhua. Research on China’s Grain Output Based on Interval Data Measurement[J].Journal of Guangxi Normal University(Natural Science Edition), 2022, 40(1): 206-215.

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Research on China’s Grain Output Based on Interval Data Measurement

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