Analysis of Economic Impact Based on Time Series Model -- Taking the GDP of Two Provinces as an Example

Abstract

Time series analysis is an important branch of statistics, which is widely used in various fields, as well as in the economic field. In the economic field, a reasonable GDP forecast helps a country to set credible, substantive, and strategic goals. In recent years, Northeast China has seen an obvious decline in the national economic ranking, and the relevant GDP data of Jilin and Heilongjiang provinces are more obvious. This paper is based on time series analysis and support vector regression (SVR) algorithm to build a series model. The model was established by using 60 GDP data of Jilin Province and Heilongjiang Province from 1959 to 2022 with similar economic facts. After calculation and verification, the optimal model of Jilin Province is ARIMA (1, 1,0), the SVR with parameter C of 10 and 2 of 0.007, and the combined model with it as the main model is the optimal model of Heilongjiang Province. The GDP of the two provinces will continue to rise in the next five years, and the GDP of Jilin Province will rise faster, and the GDP gap between the two provinces will gradually narrow.