Research On Overcapacity Evaluation And Early Warning In Steel Industry

For a long time,some local governments have been pursuing the local GDP growth,which has led to “fluctuation” in some industries.At the same time,the imperfection of the exit mechanism of enterprises has caused that the relevant surplus industries in China could not withdraw from the market in time.It results in imbalances in supply and demand,product backlog,fallen prices,lower profits and so on.The steel industry occupies the basic position in China's industrial economy.The overcapacity problem is an economic problem that has existed for a long time in China.The development of the steel industry is related to China's national economy.It is of great significant to study the overcapacity problem of the steel industry for China's supply-side structural reform.And it is also important for the healthy and sustainable development of the economy.Firstly,this thesis sorts the relevant research on the overcapacity,capacity evaluation and early warning.Then it defines the relevant concepts and sorts the overcapacity formation theory.Besides,it compares the methods of overcapacity measurement,comprehensive evaluation and early warning.Secondly,this thesis builds the model of the overcapacity assessment in China's steel industry.At first,it analyzes the external environment and internal environment of China's steel industry.Then,it explores the components of the overcapacity evaluation system of China's steel industry from the qualitative and quantitative perspectives.The VAR model is used to determine whether the environment and innovation should be the factors of the overcapacity evaluation system,and the components of the evaluation index system is determined finally.The weights of the evaluation index is determined by the entropy method-CRITIC method.At last,the overcapacity index of China's steel industry is measured by the power function method.The warning limits of early warning indicators are divided based on the 3? rules,and the early warning interval is finally obtained.All lays the foundation for the establishment of the following early warning model.Thirdly,this thesis builds the early warning model of overcapacity in China's steel industry by BP neural network through a five-step method.First,it designs an earlywarning model,and then,it trains the data of China's steel industry of 2006-2016,besides,it tests the data of 2007-2017.At last,it predicts the comprehensive index of overcapacity in China's steel industry in the next few years.According to the early warning results,decide whether to continue monitoring or to issue an early warning signal.Finally,combined with the evaluation and the early warning research,this thesis puts forward some relevant countermeasures and suggestions for government departments,markets and enterprises based on theoretical and empirical research.