The content of this book is the basic knowledge often used in the mathematical model of advanced macroeconomics, and it is indispensable for learning advanced macroeconomics. This book is divided into six chapters. After briefly introducing the commonly used mathematical knowledge of higher macroeconomics, this paper focuses on supplementing the basic mathematical knowledge of higher macroeconomics that was not involved in the undergraduate stage.

The first chapter is calculus. In addition to the knowledge of derivative, differential and integral in this science, derivative, curve integral, trigonometric series and Fourier series with parameter integral are added. In the derivation of macroeconomic models, we often encounter integral derivation with parametric variables, and curve integral, trigonometric series and Fourier series are the preparations for learning complex variable functions.

The second chapter is linear algebra. Besides matrices, vectors, linear equations and eigenvalues, the deduction of Hessian determinant and frontier Hessian determinant, matrices and quadratic forms is new. The former is necessary knowledge for judging optimization conditions, while the latter often involves dynamic optimization derivation.

The third chapter is the measure theory. Measurement theory is the basis of higher probability theory. Without the knowledge of measure theory, it is impossible to learn the axiomatic system of probability theory. We should have studied the theory of real variable function before learning the theory of measure, but this book gives a brief introduction to the theory of measure directly. Although it is only a chapter, it basically summarizes the main contents of measurement theory.