National Revenue Forecast Model Based On Data Analysis

National fiscal revenue is that the government raises money in order to perform its functions,implement public policy,and provide goods and services to the public.It is not only an important index to assess a country's financial resources,but also the premise and guarantee of the country's fiscal expenditure.Tax revenue is the main component of China's fiscal revenue.At present,our country is carrying out the tax-sharing fiscal management system.Through the division of taxes,China carries out the central-local revenue system,namely the state tax revenue and local government tax revenues are managed separately.Therefore,it is very important to establish a scientific and reasonable forecast system of national fiscal revenue.Combining the elements and structures of national financial revenue and fully taking into consideration the various influential factors of financial revenue,this paper makes use of multiple regression analysis,time sequential method,as well as Grey Model to establish forecast models.It insists on the combination of qualitative analysis and quantitative analysis,and uses data from 1995 to 2014 for empirical tests.Comparing the results of the three different methods,this paper draws the conclusion that simple exponential smoothing method is costly and effectively compared with the relatively complex models,it also cause the problem of delay;Grey model is more effective when dealing with small sample data;the regressional method could fill the structural gap of exponential method,but the linear regression has its limitations,for example,it can not describe the nonlinear relationship between variables effectively.