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This study aims to determine the effect of fintech, the amount of money in circulation, interest rates and economic growth on the analysis of digital economic trends on monetary policy in Indonesia. There are four variables in this study, namely fintech, the amount of money in circulation, interest rates and economic growth. The analysis method used is Vector Autoregression with the Impluse Response Function test or abbreviated as IRF and the Forecast Error Variance Decomposition test commonly abbreviated as FEVD, stationarity test, cointegration test, lag structure stability test and optimal lag length test. There is a contribution from each variable to the variable itself and other variables, according to the results of the Vector Autoregression study with a lag basis of 2. In addition, the results of the Vector Autoregression analysis show that the past variable (t-1) contributes to the current variable both to the variable itself and to other variables. The results of the analysis show that there is a reciprocal relationship between the variables. By using response function analysis, we can see if there is a response from other variables to changes in one variable in the short, medium, or long term. In addition, we know that the stability of all variables is formed in the short, medium, and long term. According to the Variance Decomposition Analysis, factors such as Fintech and Money Supply contribute the most to the variable itself. However, other variables that have the greatest influence on the variable itself and are supported by other variables in the short, medium, and long term are economic growth and interest rates are most influenced by Fintech.

This study aims to determine the effect of monetary policy on economic growth. This study uses the Vector Autoregression method by completing the assumption test and estimation on the research variables of inflation, investment, credit, interest rates and gross regional domestic product. Time series research data from 2003-2022 sourced from the Central Bureau of Statistics of North Sumatra (BPS) SUMUT with the results obtained are inflation and interest rates give the results that inflation is influenced by investment and credit, until investment affects gross regional domestic product. Then credit also affects inflation and interest rates and gross regional domestic product is influenced by investment and credit. Thus, in determining policies that encourage economic growth the government must consider a more coordinated monetary policy strategy to deal with the dynamics of strengthening interest rates, controlling inflation, can be measures that support economic stability.

This study examines the influence of monetary policy, particularly interest rates, on economic stability in the TIMI countries (Thailand, India, Malaysia, and Indonesia). It underscores the vital role of interest rates in controlling inflation and stimulating economic growth. Utilizing a Vector Autoregression (VAR) model, the research analyzes the reciprocal relationships between crucial economic indicators such as GDP, CPI, exchange rates, consumption, interest rates, and trade balances from 2008 to 2022. For instance, adjustments in interest rates can influence investment levels, consumption patterns, and inflation rates, thereby affecting overall economic activity. The Granger causality tests indicate that short-term relationships between these variables are insignificant, but long-term interactions are evident. This supports the Johansen cointegration results, which confirm two cointegrated equations at the 5% significance level. The study emphasizes maintaining interest rate stability for sustainable economic growth and price stability. It highlights that fluctuations in interest rates, influenced by global economic conditions and domestic economic policies, play a crucial role in the economic performance of TIMI countries. Recommendations for central banCM include implementing responsive and adaptive interest rate policies to manage inflation, foster economic growth, and maintain exchange rate stability. This approach is essential for addressing disparities in income, education, healthcare, and technology access, which are critical for equitable economic development. In conclusion, this research underscores the importance of a nuanced understanding of monetary policy's impact on economic stability and the need for coordinated efforts between fiscal and monetary authorities to achieve long-term

This research aims to determine the effect of the government expenditure model and green growth based on green energy consumption in Indonesia which has 4 variables, namely carbon emissions, energy consumption, economic growth and government expenditure. The analytical method used in this research is the Vector Auto Regression (VAR) model with the Impulse Response Function (IRF) test, Forecast Error Varince Decomposition (FEVD), stationarity test, cointegration test, structural lag stability test, and optimal lag length test. . The results of the Vector Autoregression research using lag 1 as the basis show the contribution of each variable to the variable itself and other variables. The results of the Vector Autoregression analysis also show that the past variable (t-1) contributes to the current variable, both the variable itself and other variables. From the results of the analysis, there is a reciprocal relationship between one variable and another variable. Response Function Analysis shows the response of other variables to changes in a variable in the short, medium and long term, and it is known that the stability of the response of all variables is formed within a period of 5 years or the medium term. and long term. Variance Decomposition Analysis shows that there are variables that have the largest contribution to the variable itself in the short, medium and long term, such as CO2, EC, and GOV. Meanwhile, another variable that has the greatest influence on the variable itself in the short, medium and long term is CO2 which is strongly influenced by GOV and GDP.