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| Wang, Hao. |
| Based on the research technology of scholars’ prediction of farmers’ income and the data of per capita annual net income in rural households in Henan Statistical Yearbook from 1979 to 2009, it is found that time series of farmers’ income is in accordance with I(2) non-stationary process. The order-determination and identification of the model are achieved by adopting the correlogram-based analytical method of Box-Jenkins. On the basis of comparing a group of model properties with different parameters, model ARIMA (4, 2, 2) is built up. The testing result shows that the residual error of the selected model is white noise and accords with the normal distribution, which can be used to predict farmers’ income. The model prediction indicates that income in... |
| Tipo: Journal Article |
Palavras-chave: Farmers’ income; Model ARIMA; Prediction; Time series; China; Agribusiness. |
| Ano: 2010 |
URL: http://purl.umn.edu/102374 |
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| Wang, Hao. |
| According to data of per capita net income of rural households and the per capita regional gross output from 1978 to 2008 provided by the Henan Statistical Yearbook , we know that both of the time series obey the unit root process, so they belong to non-stationary time series. The results of the Engle-Granger two-stage estimation method show that the two terms have long-term stable integration equilibrium relations. The results of Granger Causality Test show that there is only the one way Granger Causality relation from farmers’ income increase to economic growth. Connecting with the reality of Henan Province, the possible reasons are analyzed. The population of rural residents is huge and the income level of the rural residents are low, and the... |
| Tipo: Journal Article |
Palavras-chave: Farmers’ income; Economic growth; Granger Causality Test; Co-integration analysis; China; Agribusiness. |
| Ano: 2010 |
URL: http://purl.umn.edu/102383 |
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