Based On Non-agricultural Labor Practices Of The Multi-level Model Of Frontier Regions Farmers

With the policy of"Three Rural Issue"launched, more and more attention focuses on China rural economy. The key point of"Three Rural"is how to increase farmer's income. Expanding non-farm employment is one of the effective measures. Compared to the coastal mainland areas with higher level of economic development, due to various living environment and social development degrees, the rural issues of border minority region are full of particularity and complexity. This thesis, based on the frontier minorities'special status, studies the agriculture household's behavior of non-farm labor and provides some constructive suggestion for the rural economy policy special for the border minority region.This study, based on the theoretical framework of agriculture household model, considering the characteristics of farm household in border minority region, searches factors affect on non-farm labor behavior decision. It could be solved by multilevel model method for the issue on random and within-group heterogeneity which exists on agriculture household data with hierarchical structure. Meanwhile, precise explanation and conclusion could be obtained. This study provides a new analysis method for studying agriculture issue.This study carries out from two aspects as below.First, considering the agricultural census data of HongHe city, YunNan province from year 2006 to 2008 as an instance, this thesis analyses the farmer employment status of China southwest border minority region from three different angles: employment industry, agriculture category and employment area. Then, under the framework of agricultural household model, the author takes advantage of Multilevel model to study the influencing factors about the non-farm work time decision for the farm households living in the frontier minority area, at the same time, gains more exact conclusion and provides some feasible rural policy suggestion focused on the border minority region.