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Analysis of Influential Factors on Agricultural Surplus Labor Professionalization During China's Economic Downturn

Analysis of Influential Factors on Agricultural Surplus Labor Professionalization During China's Economic Downturn
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摘要 This paper contributed to the pool of studies about agricultural surplus labor in China, also acted as the root to the imminent settlement of the issues concerning agriculture, countryside and farmers. Using data from survey of agricultural surplus labor in 2012, which covered three provinces in northern, midwestem and southern parts of China, this paper analyzed the influential factors on agricultural surplus labor professionalization by adoption of a logistic regression model. It showed that agricultural surplus labor shortage could be explained by low-quality professionalization. It was a feasible and effective way to solve the issue of workforce shortage during economic downturn by improving agricultural surplus labor's professionalization. This paper contributed to the pool of studies about agricultural surplus labor in China, also acted as the root to the imminent settlement of the issues concerning agriculture, countryside and farmers. Using data from survey of agricultural surplus labor in 2012, which covered three provinces in northern, midwestem and southern parts of China, this paper analyzed the influential factors on agricultural surplus labor professionalization by adoption of a logistic regression model. It showed that agricultural surplus labor shortage could be explained by low-quality professionalization. It was a feasible and effective way to solve the issue of workforce shortage during economic downturn by improving agricultural surplus labor's professionalization.
出处 《Journal of Northeast Agricultural University(English Edition)》 CAS 2014年第1期64-69,共6页 东北农业大学学报(英文版)
关键词 agricultural surplus labor three rural issues economic downturn PROFESSIONALIZATION logistic regression model agricultural surplus labor, three rural issues, economic downturn, professionalization, logistic regression model
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