Research on Macroeconomic Analysis and Forecasting Based on Regression Models

This paper focuses on the field of macro-economic forecasting. Firstly, it expounds on the importance of macro-economic forecasting for governments, enterprises, and investors, and reviews the research history and application status of regression models in macro-economic analysis and forecasting at home and abroad. On this basis, this study adopts a comprehensive policy impact analysis method to construct an analytical framework covering fiscal, monetary, industrial, and other policies. In the research, a multiple linear regression model is used, and the principal component analysis (PCA) technique is introduced for dimensionality reduction. At the same time, this paper also evaluates the prediction accuracy of the model, analyzes the advantages and disadvantages of the multiple linear regression model, pointing out its advantages such as simple principle and low data requirements in economic forecasting, as well as limitations such as being subject to linear assumptions and ignoring complex factors. This research provides a more scientific method for macro-economic forecasting, which helps to achieve precise regulation of economic policies and the stable operation of the macro - economy.