ARIMAX多元时间序列模型在国家财政收入预测中的应用

Application of ARIMAX Multivariate Time Series Model in State Revenue Forecasting

摘要: 自1978年以来，中国的改革开放政策推动了财政收入的快速增长，并且出现了收入增长超过经济增长的局面。一个国家的财政收入是受多种因素共同影响的，其中国民生产总值是最重要原因之一。本文结合国家财政收入的结构特点，考虑国民生产总值对财政收入影响的前提下，按时间序列方法对国家财政收入建立了ARIMA和ARIMAX模型，并代入了近两年国家财政收入统计数据进行了检验，并对检验结果进行了比较分析。

Abstract: Since 1978, China’s reform and opening-up policy has pushed the rapid growth of fiscal revenues and a situation where revenue growth exceeds economic growth has emerged. A country’s fiscal revenue is affected by a combination of factors, among which the gross national product is one of the most important reasons. In this paper, combining the structural characteristics of national fiscal revenue and considering the impact of GNP on fiscal revenue, we established ARIMA and ARIMAX models for national fiscal revenue according to the time-series method, and substituted the national fiscal revenue statistics of the last two years for testing, and made a comparative analysis of the test results.