DocumentCode :
255281
Title :
Grain consumption forecasting in China for 2030 and 2050: Volume and varieties
Author :
Mingjie Gao ; Qiyou Luo ; Yang Liu ; Jian Mi
Author_Institution :
Inst. of Agric. Resources & Regional Planning, Beijing, China
fYear :
2014
fDate :
11-14 Aug. 2014
Firstpage :
1
Lastpage :
6
Abstract :
Grain consumption projections are necessary inputs for developments in infrastructure as a means to ensure national food security. In this paper, firstly, we use time series analysis to forecast the key parameters affecting grain consumption in China in 2030 and 2050, and then we employ panel data analysis to estimate the long-run demand functions for feed grain in China across a range of scenarios. Our main findings are as follows. First, we expect that per capita grain consumption (in kilograms) for urban residents increase to 355kg in 2030 and 387kg in 2050, while that of rural residents will at first decrease to 248kg in 2030, and then increase to 262kg in 2050. Second, the gross volume of grain ration and feed grain for urban grain consumption in China will be 349 million tons in 2030 rising to 416 million tons in 2050, while that for rural grain consumption will fall to 113 million tons in 2030 and 77 million tons in 2050. Third, we anticipate that other grain consumptions in China, including food processing, seed, and waste, will increase to 108 million tons in 2030 and 131 million tons in 2050. Fourth, on this basis, total grain consumption in China will be about 571 million tons in 2030 and 624 million tons in 2050. Finally, we forecast the consumption of maize, rice, and wheat in China to be 262, 154, and 114 million tons in 2030, and 318, 156 and 100 million tons in 2050, respectively.
Keywords :
agricultural products; food products; forecasting theory; time series; China; feed grain; food processing; grain consumption forecasting; grain consumption projections; grain consumptions; grain ration; long-run demand function estimation; maize consumption forecasting; national food security; panel data analysis; rice consumption forecasting; time series analysis; total grain consumption; urban grain consumption; wheat consumption forecasting; Biological system modeling; Feeds; Mathematical model; Modeling; Predictive models; Sociology; Statistics; feed grain; forecasting; grain consumption; grain ration; time series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Agro-geoinformatics (Agro-geoinformatics 2014), Third International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/Agro-Geoinformatics.2014.6910669
Filename :
6910669
Link To Document :
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