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X. Y. Wang, D. J. Liu and C. J. Qi, “The Construction of Principal Component Regression Model of Vegetables Total Output in China and Its Prediction,” Agricultural System Science and Synthetic Researches, Vol. 22, No. 2, 2006, pp. 132-138.

has been cited by the following article:

• TITLE: Optimal Choice of Cotton Subsidy Mode in China—Empirical Study Based on Principal Component Regression

  AUTHORS: Jianzhong Shi, Yuhong Li

  KEYWORDS: China; Cotton Subsidy; Import; Principal Component Regression

  JOURNAL NAME: Modern Economy, Vol.4 No.7, July 11, 2013

  ABSTRACT: Adopt principal component regression for researching the optimal subsidy mode of cotton production in China. The result indicates that, from the perspective of economic stimulatory effect, the optimal cotton subsidy in China is farm chemical subsidy rather than seed subsidy. The reason is that there are frequent pest disasters in cotton producing areas in China. So farm chemical subsidy is the most important factor ensuring cotton production. Meanwhile, cotton varieties must be optimized and improved to increase the ability to resist pests and diseases, and the forecasting for pests and diseases in cotton production areas must be enhanced, early warning mechanism and monitoring must be built, and in addition, it is strongly recommended that if financial resources allow, subsidies like seed subsidy, fertilizer subsidy, machinery subsidy and irrigation subsidy could also put into effect in China.