SYSTEMATIC APPROACH TO ANALYZING THE IMPACT OF MONETARY PROCESSES IN THE ECONOMY ON GDP.

Autor: Gumar, Nazira, Zhanibekova, Gaukhar, Imramziyeva, Munira, Zholdasbayeva, Togzhan, Bessekey, Yerkin, Kenzhin, Zhaxat
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Zdroj: Eastern-European Journal of Enterprise Technologies; 2024, Vol. 129 Issue 13, p79-90, 12p
Abstrakt: The object of the study is monetary processes and the real sector of the economy. The purpose of the study is to analyze the impact of monetary processes in the economy on GDP based on a systematic approach. The task of analyzing the relationship between the main indicators of monetary processes and GDP on the basis of a wide sample of countries was solved. The results are obtained: – for the variables included in the cluster analysis, the money supply analyzed: (1st cluster “stable financial environment” – 0, 2nd cluster “high access to credit” – 147.7, 3rd cluster “limited access to credit” – 72.2, 4th cluster “high interest rates” – 30.4 % of GDP); – 72 countries are divided into 4 clusters, with 13 countries in the first cluster, 15 in the second, 21 in the third, and 23 in the fourth. This allows to determine the nature and place of the economy in the world and to make monetary policy decisions; – there is a positive correlation between GDP and money supply (r=0.317); there is a weak positive relationship between GDP and the credit information depth index (r=0.203); there is a moderate positive relationship between GDP and domestic lending (r=0.39). Money supply management and domestic credit should be prioritized in monetary management of the economy. The obtained results are explained by the assumption of linear dependence between the indicators of monetary processes and the real sector of the economy. This assumption was confirmed on the example of different countries, which indicates its universality. The peculiarities of the results obtained are the application of a combination of cluster and correlation and regression methods of analysis using actual World Bank data [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index