A Dynamic Evaluation Model With Random Index And BayesQR Model Of China’s Food Security Were Constructed For Evaluation And Analysis

Food security is an important foundation of national security and is of great significance to national stability and development.Taking China’s food security level as the research object,this paper constructs a dynamic evaluation model with random indicators to evaluate and predict China’s food security status.On this basis,a Bayesian quantile regression model is further established to comprehensively analyze the influencing factors of food security in China.The main research content of this paper focuses on the following three parts:The first part is the construction of China’s food security index system and the analysis of basic statistical characteristics of data.Firstly,the traditional evaluation methods are summarized,their advantages and disadvantages are analyzed,and the direction is pointed out for subsequent research.Secondly,according to the connotation of China’s food security,a large number of literature is comprehensively analyzed,and 22 specific indicators such as total grain output are selected from the four perspectives of availability,availability,stability and sustainability,and the evaluation index system of China’s food security is constructed.Finally,the index data from 1985 to 2021 are selected from the National Bureau of Statistics and WIND database,and the basic statistical characteristics of the indicator data are analyzed to provide a basis for subsequent modeling.The second part is the construction and evaluation of China’s food security dynamic evaluation model with random index.In order to make the evaluation model closer to reality and reduce the complexity of statistical modeling,this paper first considers the randomness of the index,takes the amount of financial support as an example,constructs Bayesian autoregressive submodel to characterize its randomness,and calculates the expected value of the index.Secondly,considering the different focuses of countries on ensuring food security and the impact of policy introduction in different periods,the sample interval is divided into four stages,and the weights of each stage are calculated based on the improved CRITIC method,and the dynamic changes of weights are analyzed.Then,on this basis,a dynamic evaluation model of China’s food security with random indicators is constructed,and the China’s food security index is evaluated according to the model.Finally,the Markov chain was selected to predict China’s food security level from 2022 to 2025,and passed the robustness test.The results show that China’s food security level is generally on the rise,but the food security stability index shows a fluctuating downward trend,there may be trade structure problems,and the future food security situation is not optimistic.The third part is to establish BayesQR model to comprehensively analyze the influencing factors of China’s food security level.Firstly,through qualitative analysis,the main influencing factors of China’s food security are the total population,urbanization rate,total afforestation area and the exchange rate of RMB against the US dollar.Secondly,in order to comprehensively analyze the impact of various influencing factors on China’s food security level,and to improve the accuracy of parameter estimation,Bayesian method and quantile regression model are combined to construct a theoretical model of Bayesian quantile regression of China’s food security level,and the Bayes QR model of China’s food security influencing factors is obtained by setting the prior distribution,deriving the posterior distribution of each parameter full condition,and using the Gibbs sampling algorithm to estimate the parameters of the model.Finally,according to the model,the food security level of China is comprehensively analyzed.The results showed that the total population had a significant effect on China’s food security at a higher quantile level,while the urbanization rate had a significant effect on China’s food security at a lower quantile level.The total afforestation area has a more obvious inhibitory effect on China’s food security at a lower quantile level,while the exchange rate has a more obvious inhibitory effect on China’s food security at a lower and higher quantile level.