Forecast and Analysis of National GDP in China Based on ARIMA Model

Authors

  • Yiqun Liu
  • Xiao Chen
  • Qiqi Wang
  • Lipeng Zhu
  • Zejiong Zhou

DOI:

https://doi.org/10.54097/ajst.v3i2.2096

Keywords:

GDP, Time series, ARIMA model.

Abstract

Gross domestic product (GDP) is an important indicator to measure the economic situation and development level of a country or region, which is of great significance in promoting steady economic development. Therefore, this paper selects the national GDP data from 1978 to 2019, uses Eviews 9.0 software to build a model for the selected time series, and finally determines ARIMA (1, 1, 1) as the optimal model, and forecasts and analyzes the national GDP in 2020 and 2021. The prediction results show that the gap between the predicted GDP in 2020 and 2021 and the actual value is small. Therefore, ARIMA model can better reflect the development trend and short-term forecast of national GDP.

Downloads

Download data is not yet available.

References

Huang Bing, Li Wei. Analysis and prediction of residents' consumption level based on ARMA model -- taking Hunan Province as an example [J]. Marketing Circle, 2019 (46): 157-158.

Wang Shengqing. Analysis and forecast of e-commerce sales of agricultural products based on ARMA model - Eviews8.0 demonstration from Longnan data [J]. Journal of Gansu Normal University, 2017, 22 (09): 24-28.

Wang E, Zhang Ting. Application of Time Series in GDP Forecast of Hunan Province -- Based on ARIMA Model [J]. Journal of Qingdao University (Natural Science Edition), 2019, 32 (03): 136-140.

Tang Jieru, Zhu Xiaxia, Zhou Lijian. Prediction and research of population structure based on time series [J]. Journal of Jiamusi University (Natural Science Edition), 2017, 35 (04): 696-699.

Hao Yuxing. Empirical Research on Financial Support to the Development of Cultural Industry -- Time Series Data Analysis Based on Beijing [J]. Business News, 2021 (15): 87-88.

Qu Haiqing, He Xianping. Research on Hubei GDP Forecast Model Based on Time Series Analysis [J]. Journal of Hubei University of Economics (Humanities and Social Sciences Edition), 2021,18 (09): 37-39.

Wu Boni. GDP Forecast of Hangzhou City Based on Time Series Model [J]. Enterprise Reform and Management, 2019 (23): 212-213.

Guzarati. Fundamentals of Econometrics [M]. Beijing: China Renmin University Press, 2006.

Downloads

Published

28-10-2022

Issue

Section

Articles