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Prediction based on Markov chains for ladderlike rural labor transfer in Western China

机译:基于马尔可夫链的中国西部农村阶梯状劳动力转移预测

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In order to analysis and predict rural labor transfer quantitatively, a homogeneous Markov chain model of discrete parameters is proposed in this paper to describe the 三 situation of ladderlike labor transfer in western china. We consider the labor as the transfer variables and five terrain shifts the labor as variable states to build the model after carefully describe the situation of transfer. First order condition is considered to estimate transition probability matrix and estimate the parameters through Least Square method. After that, with the application of stationary distribution theory, we predict the situation of labor transfer in short term and long term. We conclude by numerical experiment that the transfer of labor in countryside is not sufficient and the current process of urbanization should be accelerated. The urban and rural dualization cannot be eliminated in current economic and policy attraction level. These quantitative results are acknowledged as essential to stimulate the local government making the situation clear and doing further work to promote the transfer.
机译:为了定量分析和预测农村劳动力转移,本文提出了一个离散参数的齐次马尔可夫链模型,描述了中国西部阶梯状劳动力转移的三种情况。在仔细描述转移情况之后,我们将劳动作为转移变量,并将五个地形转移为变量状态来构建模型。考虑一阶条件,通过最小二乘法估计过渡概率矩阵并估计参数。之后,运用平稳分配理论,对短期和长期的劳动力转移情况进行了预测。我们通过数值实验得出结论,农村的劳动力转移是不充分的,应该加快当前的城市化进程。在目前的经济和政策吸引力水平上,城乡二元化是无法消除的。这些定量的结果被认为是刺激地方政府阐明情况并开展进一步工作以促进转移的关键。

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