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Impacts of household income on beef at-home consumption: Evidence from urban China
ZHU Wen-bo, CHEN Yong-fu, ZHAO Jing, WU Bei-bei
2021, 20 (6): 1701-1715.   DOI: 10.1016/S2095-3119(20)63582-1
Abstract195)      PDF in ScienceDirect      
Beef consumption in China has increased substantially from 5.0 million tons in 2000 to 7.7 million tons in 2019 thanks to rapid income growth, but still remains low compared to pork and poultry consumption.  Improving the understanding about the impacts of household income on beef consumption in China is necessary to forecast future beef demand and inform the domestic beef industry, especially in the context of unprecedented expansion of middle income class in China.  Based on survey data of 32 878 urban households collected by the National Bureau of Statistics of China, we employed the inverse hyperbolic sine (IHS) double-hurdle model to estimate income elasticities of beef demand across different income groups and simulated possible trends of future beef consumption of Chinese urban residents.  The empirical results showed that the unconditional income elasticities of beef consumption at home vary between 0.169 for the low-income group and 0.671 for the high-income group.  The simulated results indicated that beef consumption is expected to increase by 12.0 to 38.8% in 10 years and by 18.6 to 70.5% in 15 years under distinct income growth scenarios.  Our findings provide practical insights for policy makers and other stakeholders about future beef demand, such as potential opportunities embedded in rising beef demand for domestic producers and world beef exporters as well as the urgency of improving the supply chain resilience of beef in China.
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Agricultural Policy, Climate Factors and Grain Output: Evidence From Household Survey Data in Rural China
CHEN Yong-fu, WU Zhi-gang, ZHU Tie-hui, YANG Lei, MA Guo-ying, Chien Hsiao-ping
2013, 12 (1): 169-183.   DOI: 10.1016/S2095-3119(13)60217-8
Abstract1417)      PDF in ScienceDirect      
This paper estimates a stochastic frontier function using a panel data set that includes 4 961 farmer households for the period of 2005-2009 to decompose the growth of grain production and the total factor productivity (TFP) growth at the farmer level. The empirical results show that the major contributor to the grain output growth for farmers is input growth and that its average contribution accounts for 60.92% of farmer’s grain production growth in the period of 2006-2009, whereas the average contributions sourced from TFP growth and residuals are only 17.30 and 21.78%, respectively. The growth of intermediate inputs is a top contributor with an average contribution of 44.46%, followed by the planted area (18.16%), investment in fixed assets (1.05%), and labor input (-2.75%), indicating that the contribution from the farmer’s input growth is mainly due to the growth of intermediate inputs and that the decline in labor inputs has become an obstacle for farmers in seeking grain output growth. Among the elements consisting of TFP growth, the contribution of technical progress is the largest (32.04%), followed by grain subsidies (8.55%), the average monthly temperature (4.26%), the average monthly precipitation (-0.88%), the adjusted scale effect (-5.66%), and growth in technical efficiency (-21.01%). In general, the contribution of climate factors and agricultural policy factor are positive and significant.
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