Establishment and verification of labor demand estimation model in planting industry

Xu Bing, Wang Fulin, Wang Jiquan, Zhao Shengxue

Abstract


In view of the poor precision of the theoretical model of labor demand estimation, it is difficult to estimate and predict the actual production problems accurately. Based on the actual production conditions and the relationship between the degree of mechanization of planting and the demand of labor force, this study established an estimation model for the labor demand of planting industry considering the factors of planting structure and mechanization degree. In order to ensure high reliability of data, the method of checking out abnormal data was adopted to obtain the cultivated land area index when the mechanization degree is from 0 to 100%. Taking Suihua region (Heilongjiang Province, China) as an example, the theory of the research was analyzed and applied. This study accessed to the data of cultivated land area per labor can afford when the mechanization level in Suihua area were 0 and 100% respectively through the investigation, and the average cultivated land area data of each labor force in two cases were sorted out and the abnormal data were eliminated at the same time. Finally, using the derived model, the data obtained and the mechanization level and cultivated land area of Suihua in the future, the labor demand amount in Suihua area from 2015 to 2019 were predicted. The model established in this study can be used to calculate the quantity of both current labor demand in planting industry and the labor demand in the various moments in the future through forecasting the future mechanization level and cultivated area which are the two main factors influencing the quantity of labor demand in planting structure.
Keywords: planting industry, labor, estimation model, case verification, forecast evaluation
DOI: 10.25165/j.ijabe.20171006.3094

Citation: Xu B, Wang F L, Wang J Q, Zhao S X. Establishment and verification of labor demand estimation model in planting industry. Int J Agric & Biol Eng, 2017; 10(6): 86–93.

Keywords


planting industry, labor, estimation model, case verification, forecast evaluation

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References


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