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An improved gray prediction model for China's beef consumption forecasting.

Bo Zeng1, Shuliang Li2, Wei Meng1,2

  • 1College of Business Planning, Chongqing Technology and Business University, Chongqing, PR China.

Plos One
|September 7, 2019
PubMed
Summary

Accurate beef consumption forecasting is crucial for China

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Area of Science:

  • Agricultural economics
  • Econometrics
  • Time series analysis

Background:

  • China's beef market faces supply-demand imbalances.
  • Traditional forecasting models struggle with the inherent uncertainty of beef consumption data.
  • Gray theory offers a potential solution for modeling uncertain systems.

Purpose of the Study:

  • To address structural defects in traditional gray models.
  • To develop and validate a novel gray forecasting model, EGM(1,1,r), for China's beef consumption.
  • To provide accurate forecasts to aid in balancing China's beef market.

Main Methods:

  • Analysis of structural defects in traditional gray models.
  • Development of the Enhanced Gray Model (EGM(1,1,r)).
  • Simulation and prediction of China's beef consumption using EGM(1,1,r).

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Main Results:

  • The EGM(1,1,r) model demonstrates superior simulation and prediction accuracy compared to existing gray models.
  • The study validates the effectiveness of EGM(1,1,r) for forecasting complex economic data.
  • Accurate simulation and prediction of China's beef consumption were achieved.

Conclusions:

  • The EGM(1,1,r) model offers a significant improvement for forecasting beef consumption.
  • Accurate forecasting is essential for effective policy-making in China's beef industry.
  • Findings provide a crucial reference for balancing beef supply and demand through 2025.