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• W2912170168 abstract "Using a comprehensive primary dataset collected from 3680 farmers in certain districts of China and a long-time panel dataset of 31 of China's provinces from 2000 to 2012, an empirically analyzed work is presented in this paper on the impact of farm size on agricultural technology progress from both micro and macro perspectives. A Multivariate Probit Model was built to analyze and clarify the micro basis on which farm size affects technology progress. The impact of farm size on farmers' willingness to adopt new technologies, their technical preference, and their behaviors to acquire agricultural knowledge was tested by model estimation. The influence of farmers’ average scale on agricultural technology progress in most regions was estimated by using fixed-effect and random-effect models. The progress of technology was measured by the technology progressing rate (TPR), which is calculated by the trans-log stochastic frontier function. The results show that farmers with larger farms are more willing to adopt new technologies, spend more time and money in the pursuit of agricultural knowledge, and pay more attention to productive technology rather than processing technology. From the regional analysis, it seems the regions with larger farms have a much higher technology progress rate overall, and while the effect varies depending on scale, there are remarkably positive impacts in large-farm regions, slightly negative impacts in medium-sized farm regions, and notable negative impact in small-farm regions." @default.
• W2912170168 created "2019-02-21" @default.
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• W2912170168 date "2022-07-01" @default.
• W2912170168 modified "2023-10-17" @default.
• W2912170168 title "Farm size and agricultural technology progress: Evidence from China" @default.
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• W2912170168 doi "https://doi.org/10.1016/j.jrurstud.2019.01.009" @default.
• W2912170168 hasPublicationYear "2022" @default.
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