Based on Regression Analysis and Time Series of Shaanxi Province Tourism Trend Forecast Research

Abstract

To study the influencing factors and the future development trend of tourism in Shaanxi province, China, this paper analyzes the 12-item index data of the Shaanxi tourism industry from 1990 to 2021, including the Gross Domestic Product (GDP). In this paper, the total income of tourism and the total number of tourists per year are taken as the evaluation indicators of tourism development, and the other 10 indicators are taken as the factors that may have impacts on tourism. First of all, this paper uses Principal Component Analysis (PCA) to screen these 10 variables and finds that the two indicators of GDP and the number of domestic visitors contain more than 99% of the independent variable information. Therefore, this paper takes these two indicators as independent variables, and separately takes the total income of tourism and the total number of visitors as dependent variables to design a multiple regression analysis. Then, the Autoregression Integrated Moving Average (ARIMA) model is established by time series analysis to fit the parameters and forecast the development trend of tourism in the next five years. The result of the model shows that the tourism industry in Shaanxi province is significantly impacted by COVID-19. Finally, this paper puts forward the problems and suggestions from four aspects of ecology, laws, resources, and talents to help the revival and development of Shaanxi tourism in the post-epidemic era.