Practical implementation of software automation of the BP curve and its components for the analysis of the balance of payments of Russia

This article presents a practical implementation of the balance of payments (BP) curve using the Python programming language. In this regard, this article is aimed at modeling the relationship between the interest rate, the exchange rate and the state of external economic equilibrium within the framework of the modified IS-LM-BP model. The use of numerical methods and machine learning algorithms makes it possible to analyze the dynamics of macroeconomic indicators and assess the impact of external economic factors on the country's balance of payments. The study uses real statistical data, which ensures the practical applicability of the results obtained. The leading approach to the research is the development of software code for the numerical solution of a system of equations, calibration of the model based on empirical data and the construction of forecasts on various time horizons. The materials of the article are of practical importance for using modern computational economics tools for analyzing and modeling macroeconomic equilibrium, as well as their potential in developing economic policy measures. This model is useful for strategic analysis, as it allows us to assess the impact of changes in interest rates and the exchange rate on macroeconomic equilibrium. The developed methodology allows not only to build a BP curve based on real data, but also to use it to predict future economic conditions, which makes this approach useful for macroeconomic analysis and strategic planning.

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