Yearly Grain Output Predictions in China 1980–2004

Abstract

China has a population of 1.3 billion and grain accordingly plays a crucial role in the Chinese economy. In this paper we suggest predicting grain output mainly by factor inputs and asset holding, and present a Systematic Integrated Prediction Approach (SIPA). The key elements of SIPA are an extended input–output model with assets, nonlinear variable coefficient forecasting equations, and using the minimum sum of the absolute values. Since 1980 we have used the approach to predict the yearly national grain output of China. The prediction lead time is more than half a year. The bumper, average, and poor harvests are accurately predicted every year. The average error rate over the period 1980–2004 is 1.9%.

Keywords:

• Grain output prediction
• Systematic Integrated Prediction Approach (SIPA)
• extended input–output model with assets
• nonlinear forecasting

Acknowledgements

The research was funded by the National Natural Science Foundation of China (Project No. 70131002, 60474063) and supported by the Knowledge Innovation Project of the Chinese Academy of Sciences. The authors would like to express their sincere thanks to Professors Christian DeBresson, Erik Dietzenbacher, and two anonymous referees for their valuable comments and important suggestions.

Notes

1. In areas affected by natural disasters, the actual output of crops reduces by more than 10% due to the disaster, when compared with a normal year. Areas hit by natural disasters are a subset of the areas affected by natural disasters and their actual crops' output reduces by more than 30% when compared with a normal year.

2. It can be simply proved that u _i v _i = 0, if the optimal solution exists.