Statistical Measurement of Rural Economy under Rural Revitalization Policies Based on the ARIMA Model

China's rural development has entered a new phase, where the policies for rural revitalization demonstrate both necessity and progressive significance. Concurrently, with the widespread adoption of big data, the construction of digital villages is injecting new momentum into the rural economy. Therefore, leveraging big data mining to study the rural economy under the framework of rural revitalization policies will positively promote various aspects, including agricultural structure and rural industrial development. This study employs a multiple linear regression model combined with the ARIMA time series forecasting model to analyze the impact of rural revitalization policies. Initially, the mechanisms through which rural revitalization policies affect rural development are examined from three aspects. Subsequently, the relationship between rural revitalization policies and the rural economy is explored using the multiple linear regression model, revealing a strong positive correlation between national fiscal expenditures on agriculture, forestry, and water conservancy and the GDP of the primary sector. The ARIMA model predictions and stationary sequence tests indicate that the GDP of the primary industry varies across different periods, with a notable increase in the yield rate during the new rural era, reaching 10.8%. This demonstrates that the rural revitalization policies have a significant driving effect on rural economic growth.