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Technology Adoption, Different Scale And Feeding Income:An Empirical Analysis From The 462 Pig-Farmers In China

Xin Deng, YanBin Qi, Yong Chen


From the perspective of Pig-farmer’s conditions and different feeding scale,we focus on the followings: Dose technology adoption exist significantly difference which arises from different conditions for pig-farmers? And does technology adoption improve the level of feeding income significantly? And dose technology adoption exert significantly influence on feeding income for the pig-farmers with different feeding scale? Therefore, selective bias is usually excluded by most of studies. Basing on the data from the 462 Pig-farmers in Sichuan Province, and using the endogenous switching regression model with the method of average treatment effect, we get some truths as following: Firstly, the farms whose family is in the dry tree perfect to adopt the technology. Secondly, the pig-farm’s income can be improved by adopting technology. Finally, comparing with the small pig-farmers, the big pig-farmer’s income can be improved to higher level.


Technology adoption; income level; different scale; the endogenous switching regression model; the method of average treatment effect

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Chen Yuping, Wu Haitao, Sushil Pandey, et al. The Effect of Technology Adoption on Income Distribution among Farmers: Evidence from the Southwest of Yunnan Province [J]. China soft science, 2009 (07): 35-41.

Cunguara B, Darnhofer I. Assessing the impact of improved agricultural technologies on household income in rural Mozambique[J]. Food Policy, 2011,36(3):378-390.

Huang Jihuang. China Agricultural Development for Sixty Years and Thirty Years of Reform Miracle-- System Innovation, Technological Progress and Market Reform [J].Agricultural Technology and Economy, 2010 (01): 4-18.

Kabunga N S, Dubois T, Qaim M. Impact of tissue culture banana technology on farm household income and food security in Kenya[J]. Food Policy, 2014,45(45):25-34.

Liu Xiaohong, Wang Jian, Liu Changchun, et al. Analysis on the Standardized Breeding Mode and Technical Level of Pig Breeding in China [J] .Chinese Journal of Agricultural Science and Technology, 2013 (06): 72-77.

Lokshin M, Sajaia Z. Maximum Likelihood Estimation of Endogenous Switching Regression Models[J]. Stata Journal, 2004,4(3):282-289.

Han Yijie, Liu Xiuli. The Predicted Impact of Price Fluctuation of Chinese Pork on the Price and CPI of Other Departments [J].CPI China rural economy, 2011 (05): 12-20.

Kathage J, Qaim M. Economic impacts and impact dynamics of Bt (Bacillus thuringiensis) cotton in India.[J]. Proceedings of the National Academy of Sciences, 2012,109(29):11652-11656.

Li Dasheng, Li Qin. Mechanism and Empirical Study on the Impact of Agricultural Technology Progress on the Income Gap between Farmers [J]. Agricultural Technology and Economy, 2007 (03): 23-27.

Li Xiaonan, Li Rui, Luo Bangyong. Effects of Agricultural Technology Training and Non-agricultural Vocational Training on Rural Residents' Income [J]. Mathematical Statistics and Management, 2015 (05): 867-877.

Liu Yuchun,Xiu Changbai. Rural Financial Development, Agricultural Science and Technology Progress and the Growth of Farmers' Income [J]. Agricultural Technology and Economy, 2013 (9): 92-100.

Lu Wencong, Yu Xinping. China's Agricultural Science and Technology Progress and the Growth of Farmers' Income [J].Journal of Zhejiang University (HUMANITIES AND SOCIAL SCIENCES), 2013 (04): 5-16.

Ma chenglin, Zhou Deyi. An Empirical Study on the Scale Growth and Technical change of Pig Breeding in China [J]. Journal of Huazhong Agricultural University (SOCIAL SCIENCE EDITION), 2014 (04): 30-35.

Ma W, Abdulai A. Does cooperative membership improve household welfare? Evidence from apple farmers in China[J]. Food Policy, 2016,58:94-102.

Pan Dan. Effects of agricultural Technology Training on Rural Residents' Income: a Propensity Score Matching Approach [J]. Journal of Nanjing Agricultural University (SOCIAL SCIENCE EDITION), 2014 (05): 62-69.

Qian Dingwei. New Varieties of Tea Technology Diffusion Effect on the Income of Different Households -- Taking Tea Farmers in Fujian Province as Examples [J].Agricultural Technology and Economy, 2012 (03): 65-70.

Wang Aimin,Li Zilian. Research on the Impact Mechanism of Agricultural Technology Progress on Farmer s ' Income [J]. Economic Survey, 2014 (04): 31-36.

Wang Yulin, Liu Guojiang, Li Houjian, et al. Analysis on the Influencing Factors of Farmers' Continuing to Engage in Pig's Feeding Behavior: Based on the Investigation of 25 Counties (cities, districts) in Sichuan province [J]. China rural area, 2015 (5): 85-96.

Wu Delin, Zhang Ping. Are Agricultural science and technology investment reasons to form the "Matthew effect" of farmers’ income? [J]. Agricultural technology and economy, 2015 (04): 61-68.

Yifu Lin. System, Technology and the Development of Agriculture in China [M].Shanghai Joint Publishing Company, 1992

Zhang Zhaohua. Income Discrepancy, the Degree of Technology Adoption and Farmers' Income Change -- Based on the Investigation of Five Counties of Eastern and Northern Guangdong[J].Finance Journal, 2013 (06): 9-14.

Zhou Bo,Yu Leng. The Impact of Agricultural Technology Application on Farmer's Income -- Taking a Study on the Observation of Farmers in Jiangxi Province as an Example [J]. Chinese rural economy 2011 (01): 49-57.


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