Abstract
The income of rural residents is not only an important indicator to measure the development of rural economy, but also a key factor in the livelihood of farmers. The accurate prediction of income of rural residents can provide data supporting for promoting rural revitalization strategy. This paper selects per capita disposable income of rural residents in China as the research object and uses the macrostatistical data from 2011 to 2020 to predict farmers’ income. Firstly, the grey prediction model is constructed, and the grey prediction value is corrected by Markov chain. The simulation value is compared with the real value. And the results show that the prediction accuracy of the model is higher. It shows that the results of using the grey Markov model to predict the income of rural residents in China from 2021 to 2025 are reliable. Finally, the article puts forward policy recommendations to promote the income of rural residents.
Highlights
Erefore, China proposes to fully implement the strategy of rural revitalization and is committed to solving various problems in the process of rural development, so as to promote the synchronous development of rural and urban areas and accelerate the pace of urban-rural integration [2, 3]
Introduction e income of rural residents is an important indicator to measure the development of rural economy, and a key factor in the livelihood of farmers
Farmers’ income mainly comes from agricultural production and wage income. erefore, the focus of future work in rural areas of China is to realize industrial prosperity according to the strategy of rural revitalization, so as to promote the continuous improvement income of rural residents [8]. e income of farmers is an important symbol of rural development level and farmers’ living conditions
Summary
The research on farmers’ income mainly includes influencing factors and trend prediction. Many scholars have found that there are many factors affecting the income growth of farmers. E results showed that the use of the Internet will directly affect the growth of farmers’ income. It is the main source of income for farmers by agricultural production, and it will affect crops because of climate and environmental changes. Zhang et al [20] used time series method to forecast financial revenue in China They considered the influencing factor of inflation in the prediction and used the consumer price index to eliminate the impact of inflation. By studying the case of per capita disposable income in Hebei Province, Wang found that the sample length will affect the use of grey prediction model, which is not suitable for predicting the case of too long sample length [24]. erefore, we should pay attention to the sample length when using the grey prediction model
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