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CONSTRUCTION OF THE IS CURVE BASED ON MACROECONOMIC DATA OF THE RUSSIAN ECONOMY 2011-2022 (I QUARTER) USING PYTHON FOR PRIMARY DATA ANALYSIS AND REGRESSION RELATIONSHIPS OF MODEL COMPONENTS

Shchegolev Alexey Vladimirovich  (Applicant for the scientific degree of Candidate of Sciences, JSC “NPC ASPECT” Dubna )

This study conducts an analysis of Russia's macroeconomic data spanning from 2011 to the first quarter of 2022, aiming to construct the IS curve—an integral component of the IS-LM model. Leveraging Python programming tools, the research presents a methodology for primary data analysis and the establishment of regression dependencies for the elements of this model. The dataset employed in this research comprises pivotal macroeconomic variables, including GDP, investments, and interest rates, allowing for an in-depth exploration of the impact of these factors on the Russian economy. Utilizing Python tools such as pandas, numpy, and matplotlib, the study conducts data analysis and constructs the IS curve, facilitating a better comprehension of the interrelationships among income, interest rates, and investment levels within the economy. This article is intended for professionals in the field of economics, analysts, and researchers interested in employing programming for the analysis of macroeconomic data. The presented analysis extends new perspectives for understanding the factors influencing economic processes in Russia and demonstrates the application of contemporary data analysis tools in macroeconomics.

Keywords:IS curve, macroeconomic data, Python, primary data analysis, regression dependencies, GDP, investments, interest rates, libraries: pandas, numpy, matplotlib
 

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Citation link:
Shchegolev A. V. CONSTRUCTION OF THE IS CURVE BASED ON MACROECONOMIC DATA OF THE RUSSIAN ECONOMY 2011-2022 (I QUARTER) USING PYTHON FOR PRIMARY DATA ANALYSIS AND REGRESSION RELATIONSHIPS OF MODEL COMPONENTS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№01/2. -С. 81-93 DOI 10.37882/2223-2966.2025.01-2.21
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