ANALYSIS OF THE RELATIONSHIP BETWEEN MACROECONOMIC INDICATORS BASED ON THE VAR (VECTOR AUTOREGRESSION) MODEL

Abstract

Annotation:                                                                                                        This article explores the application of the VAR (Vector Autoregression) model in analyzing the interrelationships among macroeconomic indicators. The VAR model is one of the modern econometric analysis methods that allows identifying dynamic relationships between multiple variables and studying their mutual influence in depth. Examining the interactions among macroeconomic indicators — such as Gross Domestic Product (GDP), inflation rate, interest rate, investment volume, and exchange rate — plays an important role in shaping economic policy, national planning, and ensuring financial stability.                                    The paper provides a detailed discussion of the mathematical foundations, structure, and practical use of the VAR model. A key feature of the model is its ability to identify causal relationships (Granger causality) among variables. The article also explains the process of preparing time series data, building the model, selecting the lag order (AIC, BIC), and applying analytical tools such as Impulse Response Function (IRF) and Variance Decomposition for deeper interpretation.                 Using real data from the economy of Uzbekistan, the relationships between GDP, inflation, and interest rate are analyzed through the VAR model. The results indicate a strong interconnection between these macroeconomic variables. The study highlights the importance of the VAR model in developing macroeconomic policies, supporting decision-making processes, and assessing economic stability.                   This work will be useful for students of econometrics, researchers, and professionals involved in economic policy, serving as an effective methodological tool for understanding, forecasting, and analyzing macroeconomic processes.