A Grey-Markov predication for unemployment rate of graduates in China

Influenced by a number of uncertain factors, Unemployment rate of college graduates has characteristics of stochastic nature and fluctuations. Single gray GM (1,1)model could not fit these data better, and its forecasting accuracy is lower. However, Markov forecast can make up for this deficiency. Drawing on the virtue of gray model and Markov forecasting model, this paper presents a grey-Markov forecasting model for forecasting unemployment rate of graduates in China. This method takes into account the general trend series and random fluctuations about this trend. It has the merits of both simplicity of application and high forecasting precision. This paper is on basis of historical data of the unemployment rate of graduates in China, and forecasts and analyzes the unemployment rate of graduates in China in terms of grey-Markov forecasting model.