Forecasting domestic credit growth based on ARIMA model: Evidence from Vietnam and China

• Main Author: Doan Van Dinh
• Format: Article
• Language: English
• Published: Growing Science 2019-11-01
• Series: Management Science Letters
• Subjects: autoregressive model; autoregressive integrated moving average; credit growth; domestic credit; moving average
• Online Access: http://www.growingscience.com/msl/Vol10/msl_2019_327.pdf
• ISSN: 1923-9335; 1923-9343

Credit is an economic category and is also a product of the commodity economy, which exists through many socio-economic forms to promote economic growth. Therefore, the objective of this paper is to analyst, compare and forecast domestic credit growth in Vietnam's and China's economy. Thus, the paper is applied by a method of an autoregressive integrated moving average (ARIMA) model. This model is fitted to time series data both to better understand the data and to forecast future points in the series. Hereby, the methodology is selected by Vietnam's bestfit model ARIMA (2,3,1) and China's best-fit model ARIMA (2,3,5). Analytical data are collected from 1996 to 2017, the sample fitted the model and is statistically significant. The result show the forecast result for next years. The Vietnamese and Chinese economy are the open economies and have domestic credit greatly contributed to economic growth. These results are the basis for policymakers to have a general view and define the impact of domestic credit growth on GDP between the two countries.