Research On Monitoring System And Analysis System In Early Warning System Of Unemployment

Employment is a major issue related to the national economy and people’s livelihood.Through the efforts of governments at all levels,the employment situation has remained stable.However,due to the downward pressure on China’s economy,the adverse international trade environment and other factors,the employment sector is also facing many risks.How to correctly judge the current employment situation and prevent the large-scale unemployment for a period of time in the future is an urgent problem for governments at all levels.Based on the research of domestic and foreign scholars and many years of employment work,referring to the economic early warning theory,unemployment early warning theory and market failure theory,this study constructs and designs a set of unemployment early warning system suitable for Panzhihua City,and verifies the feasibility of the unemployment early warning system with the actual data of Panzhihua City.According to the results of early warning and prediction,it provides a strong basis for the relevant departments of the municipal government to formulate and implement policies,and lays a foundation for preventing and resolving unemployment risks.Firstly,the comprehensive unemployment rate is constructed on the basis of the registered unemployment rate,the survey unemployment rate and the rate of job loss,which can be used as the benchmark index to judge the unemployment situation and reflect the unemployment situation more comprehensively and accurately.Secondly,from the four dimensions of employment and unemployment,labor resources,economic operation and policy guarantee,20 indicators with high correlation with the comprehensive unemployment rate are selected to build the monitoring index system.The threshold method is used to construct the employment and unemployment index,the labor resource index,the economic operation index and the policy guarantee index to find the reasons for the alarm.Thirdly,the leading indicators of the comprehensive unemployment rate are selected from the four dimensions of employment and unemployment,labor resources,economic operation and policy guarantee.Based on the sample data from the first quarter of 2011 to the fourth quarter of 2018,and according to the characteristics that the leading indicators precede the benchmark indicators,the comprehensive unemployment rate in the next three periods is predicted by ARIMA model,multiple linear regression model and BP neural network model,Through the verification of the data in the first and second quarters of 2019,the prediction error is within 10%.On this basis,the combination prediction method is used to optimize the prediction model,improve the prediction accuracy,and control the prediction error within 5%.Finally,we use the 3σ method to define the warning line and warning interval,and adjust the warning line and warning interval according to the new comprehensive unemployment rate in each period.According to the unemployment warning line and warning interval defined for each period,the comprehensive unemployment rate from the fourth quarter of2018 to the second quarter of 2019 is in a safe area,and there is no unemployment warning.According to the prediction results of the second quarter of 2019 and the division of warning line and warning interval,there is no unemployment alarm from the third quarter of 2019 to the first quarter of 2020.There are three main innovations in this paper.First,the registered unemployment rate,the surveyed unemployment rate and the rate of job loss are used to construct the comprehensive unemployment rate as the benchmark index to judge the unemployment situation,which overcomes the limitation of a single unemployment rate index in reflecting the unemployment situation.Secondly,on the basis of selecting three prediction models to predict the comprehensive unemployment rate,the combined prediction method is used to improve the prediction accuracy and judge the unemployment situation in the future more accurately.Finally,the 3σ method is adopted to determine the warning range and warning line,which can not only judge the unemployment situation but also adjust the warning line according to the changes of indicators.