农村剩余劳动力估算的工日法的分析与改进研究

在现有文献研究的基础上,对估算农村剩余劳动力的工日法又作了进一步深入研究,给出了该方法的计算模型,指出了工日法存在的不足,即没有考虑农业生产的季节性、阶段性和气象因素对农业生产的影响.按照工日法估算的农业劳动力需求数量与农业生产实际需要量有较大的偏差,会出现在作业高峰期劳动力不够用,在农闲季节,本无劳动任务,却认为在劳动的情况,并通过示例计算,对其进行了验证.在此基础上,研究给出了一种改进方法,即作业高峰期法,同时给出了该方法的数学模型.该方法不仅考虑了农业生产的季节性和阶段性,同时也考虑了气象因素对农业生产的影响,因此能够较好地反映农业生产实际.最后探讨了估算不同区域范围农村剩余劳动力的估算方法,同时提出了在研究全国的农村剩余劳动力数量时,应根据农业生产、地域和气候等特点,将全国划分成若干个类型区,然后在不同的区域上分别进行抽样调查,获取相应的数据,分别进行计算,最后加总得出全国的数据.而在研究一个地区或一个县的剩余劳动力则一般可不进行分区.

Study on Labor-Days Method of Estimation Rural Surplus Labor Force Analysis and Improvement

Based on the existing literature,This paper makes further study of the estimating the method of man-days of rural surplus labor and gives the calculation model of this method,and points out the shortcomings of this method—without taking into account of the factors which impacts on agricultural production,including seasonal,stage and meteorological factors,according to the method of man-days,there is a large deviation between the estimate and actual demanding labor.Labor will be not enough on the peak of working. In the slack season,there is no any working,but this situation is considered on working.So this paper authenticates it by calculating examples.On this basis,this paper researches an improved method,called the peak operation method,and giving the mathematical model at the sametime.This method takes into account of not only the seasonal and stage of agricultural production,but also the impacting of meteorological factors.So it will better reflect the actual agricultural production.Finally,this paper discusses the estimation method of the rural surplus labor force in different regions.In the studying of the number of rural surplus labor,it should be based on the characters of agricultural production,geographical and climate.The country is divided into several zones,and made sample survey respectively in different regions to obtain the corresponding data.After calculating and obtaining the national data finally.But in the study of one region or one county's surplus labor is generally may not be partitioned.